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INTRODUCTORY LECTURE UVODNO PREDAVANJE Proceedings 2010. (2011), Vol 2, ISSN 1986-8154 www.sportkon.com SPORT I VEŠTAČKA INTELIGENCIJA SPORTS AND ARTIFICIAL INTELLIGENCE \orđe Stefanović1 Fakultet sporta i fizičkog vaspitanja, Beograd, Srbija Faculty of Sport and Physical Education, Belgrade, Serbia 1 INTRODUCTORY LECTURE doi: 10.5550/SP.2.2010.04 UDK: 796.371.214(437.6)(4) UVODNO PREDAVANJE COBISS.BH-ID: 2246936 Summary Sažetak The rapid development of computer technologies influenced the necessity to introduce changes in sport domain. Artificial intelligence represents a branch within computational science which has the task to create computers that can reason in a way similar to human behavior. The aim of this work is to explain how artificial intelligence can support sport in an increasingly complicated and demanding sports environment. Due to a large number of efficient and reliable solutions, several areas in the domain of artificial intelligence have become relevant to the process of sport development. Some of them will be dealt with in this work: expert systems, game theory, neurological networks and software agent/based modeling. Nagli razvoj kompjuterskih tehnologija uticao je potrebu da se uvedu promene i u sferi sporta. Ve{tačka inteligencija predstavlja računarsku disciplinu čiji je zadatak da stvori računare koji mogu da rezonuju na način sličan ljudskom rezonovanju. Ideja ovoga rada je da se objasni kako ve������������������� {������������������ tačka inteligencija pomaže (mogućnosti i olak������������������������������ {����������������������������� ice) sportu u sve komplikovanijem i zahtevnijem sportskom okruženju. Usled velikog broja efikasnih i pouzdanih re{enja pojavile su se vi{e oblasti ve��������������������������������������������������� {�������������������������������������������������� tačke inteligencije koje su postale bitne u procesu razvoja sporta. Neke od njih će biti predmet razmatranja u ovom radu: ekspertni sistemi, igre, neuronske mreže i softverski agenti. Key Words: sport, artificial intelligence, expert systems, games theory, neurological networks, software agents. Ključne riječi: sport, ve�������������������������������������� {������������������������������������� tačka inteligencija, ekspertni sistemi, igre, neuronske mreže, softverski agenti. Introduction to the area of the artificial intelligence Uvođenje u prostor ve{tačke inteligencije Artificial Intelligence (AI) is a branch of computer science with the objective to create computers with the ability of reasoning in a similar way to human beings. The AI deals with the development of programs which show intelligence similar to the human’s. Basically, AI means processing of knowledge, not of data. The objective of AI in sports is to explain how its application may help in more and more complicated and demanding sports environment. In other words, the idea of this paper was to show the possibilities and conveniences which are provided by the application of the AI in sports. In our days, it is expected to have a quick reaction to changes and problems in sports, both on the research and practice level. AI-based systems allow, at least in some segments, a quicker and more accurate obtaining of necessary information, and, which makes them different, to completely substitute routine tasks of a coach in some cases. Although computers are far from being able to imitate human thinking, they stand out by logical processes – which Garry Kasparov (world chess champion) could see for himself in 2003 during the chess match against the computer Deep Junior (Figure 1). AI trend is reflected in several aspects. Some experts find that the technology will go so far that it will allow a Human Nervous System to be connected to a computer. It has been already evidenced that human beings could control a com- Ve{tačka inteligencija (Vi) predstavlja računarsku disciplinu čiji je zadatak da stvori računare koji mogu da rezonuju na način sličan ljudskom rezonovanju. Ona izučava razvoj programa koji pokazuju inteligenciju nalik na ljudsku. U osnovi, Vi podrazumeva procesiranje znanja, a ne podataka. Cilj Vi u sportu je da se objasni kako njena primena pomaže u sve komplikovanijem i zahtevnijem sportskom okruženju. Drugim rečima, ideja pisanja bila je da se prikažu mogućnosti i olak{ice koje daje primena Vi u sportu. Danas se očekuje brza reakcija na nastale promene i probleme na polju sporta, kako na istraživačkom planu tako i u praksi. Sistemi zasnovani na Vi omogućavaju, bar u nekim delovima, tačnije i brže dobijanje potrebnih informacija, a ono {to ih čini posebnim, je to {to u nekim slučajevima i potpuno zamenjuju rutinske zadatke trenera. Iako su kompjuteri daleko od opona{anja ljudskog razmi{ljanja, oni se ističu logičkim postupcima – u {ta se Gari Kasparov (svetski prvak u {ahu) uverio 2003. tokom {ahovskog meča s kompjuterom „Dip Džunior“ (Deep Junior) (Slika 1). Trend Vi se ogleda u nekoliko aspekata. Neki stručnjaci smatraju da će tehnologija otići toliko daleko da će omogućiti da ljudski nervni sistem bude povezan sa kompjuterom. Već je pokazano da ljudi mogu upravljati kompjuterima 22 Stefanović, \.: SPORT I VE[TAČKA INTELIGENCIJA Zbornik radova 2010, 22-33 puter with nothing but their thoughts, using electrodes attached to the scalp, or wires connected to their nerves. Such technology could help in designing perfect artificial limbs, or hands, and enable making more complex movements. Improvements of our bodies are the area of interest for the AI. As a result, prosthetic body parts nowadays serve solely for reconstructive purposes; they restore body function of their users, which was lost due to illness or injury. Some believe that the Evolution of Cyborgs (half machineshalf humans, as in the movie “Terminator”) is not only inevitable, but also necessary. They perceive a future in which people will have to either integrate with machines or to accept the domination of robots. Others imagine future humans who would improve their abilities using external devices instead of implants. Maybe we will become surrounded by more and more gadgets, such as palm computers or smart phones, in enormous wireless network which would enable us to be constantly connected to the Internet and to each other. In 2020, a home will have its own machine for virtual reality – virtual Robo-Pal (Figure 2). This machine will allow family members to play dangerous sports such as mountain climbing, or bungee-jumping, but also to visit exotic places during their virtual vacation, all that with one click. A virtual station joints together the mind-control technology and artificial sensor feedback. Rising trend of miniaturization will eventually result in miniature computers that can be sewn into clothes. Scientists are even now developing computers which can be washed, made of fabrics which conduct current. These fabrics contain a microchip, and they are supplied by solar energy, or by devices producing electricity from body movements. Figure 3 shows computerized clothes – the “smart” jacket, which contains a microchip, keyboard made of fabrics, on one of the sleeves. It is supposed that sportsmen will be able to use it too. Which subfields are within the AI? A large number of efficient and reliable solutions were invented and improved. This explains why AI is divided into a number of subfields, from shape recognition to artificial life, including evaluative calculation and planning. The syncretism of AI and sports can INTRODUCTORY LECTURE UVODNO PREDAVANJE Slika 1: Gari Kasparov u {ahovskom meču s kompjuterom Figure 1: Garry Kasparov in the chess match against the computer samo pomoću misli, koristeći elektrode pričvr{ćene za kožu lobanje, ili žice koje su povezane s njihovim nervima. Takva tehnologija mogla bi pomoći u pravljenju savr{enih ve{tačkoh udova, ili {aka, omogućavajući sve složenije pokrete. Usavr{avanje na{eg tela je prostor u kome je Vi na{la interesovanje. Tako protektički delovi tela danas služe isključivo u rekonstruktivne svrhe; svojim korisnicima vraćaju telesnu funkciju koja je izgubljena usled bolesti ili povrede. Neki smatraju da evolucija kiborga (bića koja su pola ma{ine, a pola ljudi, npr. u filmu “Terminator“) nije samo neizbežna, već i neophodna. Oni vide budućnost u kojoj će ljudi morati, ili da se spoje s ma{inama, ili da prihvate dominaciju robota. Drugi zami{ljaju buduće ljude koji će unaprediti svoje sposobnosti putem spoljnih naprava umesto implantata. Možda ćemo postati okruženi sve većim brojem spravica, kao {to su kompjuteri veličine {ake i inteligentni telefoni, ogromne bežične mreže putem kojih ćemo neprestano biti u univerzalnom kontaktu sa Internetom i jedni s drugima. Dom iz 2020. imaće vlastitu ma{inu za virtuelnu stvarnost – virtuelni robopal (Slika 2). Pomoću nje, članovi porodice moći će da upražnjavaju opasne sportove kao ������������� {������������ to su planinarenje, ili skakanje na bandžiju, kao i da posećuju egzotična mesta tokom virtuelnog godi{njeg odmora, a sve to na pritisak dugmeta. Virtuelna stanica spaja tehnologiju upravljanja mislima i ve{tačku senzornu povratnu spregu. Trend minijaturizacije na kraju će proizvesti siću{ne računare koji će moći da se u{ivaju u odeću. Naučnici čak razvijaju računare koji se mogu prati, a koji su napravljeni od tkanina koje provode struju. Te tkanine sadrže mikročip, a napajaće se solarnom energijom, ili uređajima koji stvaraju elektricitet od pokreta tela. Na Slici 3 je prikazana kompjuterizovana odeća – „pametna“ jakna, koji sadrži mikročip, tastaturu od materijala na jednom rukavu. Pretpostavka je da će moći da je koriste i sportisti. Koje oblasti čine prostor Vi? Veliki broj efikasnih i pouzdanih re{enja se pojavio i unapredio. Ovo daje obja{njenje za{to je Vi podeljena na vi{e grana, od prepoznavanja oblika, do ve{tačkog života, uključujući evolutivno izračunavanje i planiranje. Sinkretizam Vi i sporta moguće je da se objasni 23 INTRODUCTORY LECTURE UVODNO PREDAVANJE Stefanović, \.: SPORTS AND ARTIFICIAL INTELLIGENCE Proceedings 2010, 22-33 be explained through a short introduction to fields such as: expert systems in sports, electronic games, neural networks and software agents. kroz kraće upoznavanje sa oblastima kao {to su: ekspertni sistemi u sportu, elektronske igre, neuronske mrže i softverski agenti. Slika 2: Virtuelni robopal Figure 2: Virtual Robo-Pal Slika 3: „Pametna jakna“ Figure 3: „Smart jacket“ Expert systems and sports Ekspertni sistemi i sport The demand for Expert Systems (ES) has been growing as the rhythm of people’s life became faster; on the other hand, the “loss” of time in waiting for experts in specific fields to come and try to solve or help in solving certain problems. ES is a computer program which emulates problem solving in the way an expert does it. In order to be named an ES, a program has to contain expert knowledge in the specific field and to provide automated reasoning. ES is developed using relevant software tools (shell). The development of ES involves an expert, knowledge engineer and a user (Figure 4). An Expert (lat. expertus) is a professional, adept, master in a given subject. Who is an expert in sports? Usually a distinguished professor – scientist/researcher among internationally recognized national and foreign university lecturers. His/her role is to: “lend” (give, transmit) knowledge and assist in the verification (testing) of ES’s knowledge. Problems may occur if the expert is: inaccessible, uncommunicative; if he tends to emphasize the obvious and cannot remember everything. Knowledge engineer is a person who interviews the expert and collects (“retrieves) knowledge from him/her. Then the person is supposed to select appropriate techniques for presenting the knowledge and appropriate techniques for deduction; to select the development tools, formalize, formulate and systemize the expert’s knowledge and finally to test the ES. A Sports Technologist is to sports is what a knowledge engineer is to the AI. A User utilizes the finished ES, participates in making requests, and can also participate in testing and writing the ES documentation. In sports, users are usually a coach and a sportsman. ES can be applied to various tasks in sports: Potreba za ekspertnim sistemima (Es) se povećavala kako se ubrzavao tempo života ljudi, a sa druge strane skratilo se „gubljenje“ vremena u čekanju da dođu ekpserti određenih profila i poku������������������������������������������� {������������������������������������������ aju da re��������������������������������� {�������������������������������� e ili pomognu oko određenih problema. Es je računarski program kojim se emulira re{avanje problema na način na koji to čini ekspert. Da bi neki program mogao da se nazove Es mora da sadrži ekspertsko znanje iz neke oblasti i da omogućava automatizovano rezonovanje. Es se razvija kori{ćenjem odgovarajućih softverskih alata (shell). U razvoju Es učestvuju ekspert, inženjer znanja i korisnik (Slika 4). Ekspert (lat. expertus) je stručnjak, poznavalac, majstor u čemu. Ko je ekspert sportu? To je najče{će istaknuti profesor – naučni radnik iz redova međunarodno priznatih domaćih i inostranih univerzitetskih nastavnika. Njegova uloga je da: „pozajmljuje“ (daje, prenosi) znanje i pomaže pri proveri (testiranju) znanja Es. Problemi su ako je ekspert: nedostupan, nekomunikativan, sklon tome da ističe očigledno i ne može da se seti svega. Inženjer znanja (engl. knowledge engineer) je čovek koji vodi intervju sa ekspertom i od njega prikuplja („izvlači“) znanje. Zatim vr{i izbor odgovarajućih tehnika za predstavljanje znanja, vr{i izbor odgovarajućih tehnika za zaključivanje, vr{i izbor razvojnog alata, formalizuje, formuli{e i sređuje ekspertovo znanje i na kraju testira Es. Ono {to predstavlja inženjer znanja u Vi, to je tehnolog sporta u sportu. Profil takvog čoveka je značajan za sport, jer je bitno da postoji neko ko je obrazovan i da može da prenosi znanja iz nauke/teorije u praksu sporta. Korisnik koristi gotov Es, učestvuje u formiranju zahteva, a može da učestvuje u testiranju i pisanju dokumentacije za Es. U sportu su korisnici Es najče{će trener i sportista. Es mogu da se primene na različite zadatke u sportu: •Stvaranje podsetnika i generisanje alarma. U tzv. ril-tajm (real-time) situacijama, Es povezan sa monitorom može 24 Stefanović, \.: SPORT I VE[TAČKA INTELIGENCIJA Zbornik radova 2010, 22-33 •Creating reminders and generating alerts. In so-called real-time situations, ES connected to a monitor may warn about changes in the player’s condition. For example, in the beginning of preparations of a football team, the coach gave to the players a task to move around the field in the aerobic zone of load intensity with specified TE-TA tasks. If one of football players is not within the required range of pulse load, the coach will remind him to increase or decrease his motion speed. •Assistance in establishing diagnoses. When the case of a sportsman is complex, rare or the person establishing a diagnosis simply does not have enough experience, ES may help in getting to the most probable diagnosis based on the information. •Analysis and planning of training. ES can either search for contradictions, errors and failures in the existing training plan and program, or it may use the analysis of the specific sportsman’s condition for determining a treatment, based on the adopted training instructions. •Agents for finding information. Software agents may be sent to search and deliver information, e.g. on the Internet. Agents have knowledge on user’s preferences and needs, and they may also have some knowledge on sports, in order to be able to evaluate the relevance and usefulness of their findings. • Recognition and interpretation of images. Many images in the form of curves (e.g. Pulse load) can be automatically interpreted, including standard and more complex images. Details about a sportsman are inputs, and outputs represent the diagnosis – recommended training methods, means and loads during a training. ES were not created with a view to replacing completely professionals, coaches, but rather as big support. This is the way in which Omega Wave Sport Technology System (OW) works. This system carries out the analysis of a sportsman / team in respect of body and mental loads for the purpose of the optimization of the training process. OW analyzes the electrical activity in the heart and slow brain waves in order to create an “internal image” of how the sportsman body functions. Thereat, OW does this very fast, in a non-stressful and non-invasive way. For the first time ever, sportsmen, coaches, physiologists and scientists can monitor cycles of stress and recovery of their players on daily basis. With OW, it is nowadays possible to follow, INTRODUCTORY LECTURE UVODNO PREDAVANJE Slika 4: Učesnici u razvoju i korišćenju ES u sportu Figure 4: Participants in the development and utilization of ES in sports da upozori na promene stanja sportiste. Npr. trener je na početku priprema fudbalske ekipe zadao da se svi igrači kreću po terenu u aerobnoj zoni intenziteta opterećenja sa definisanim TE-TA zadacima. Ukoliko se neko od fudbalera ne nalazi u zadatom opsegu pulsnog opterećenja, trener ga opomene da poveća ili smanji brzinu kretanja. •Asistencija u postavljanju dijagnoza. Kada je slučaj sportiste kompleksan, redak ili osoba koja postavlja dijagnozu, jednostavno, nema dovoljno iskustva, Es može pomoći da se dođe do najverovatnije dijagnoze na osnovu podataka. •Analiza i planiranje treninga. Es može, ili da traži protivrečnosti, gre������������������������������������������� {������������������������������������������ ke i propuste u postojećem planu i programu treninga, ili može da koristi analizu specifičnog stanja sportiste za određivanje tretmana koja je bazirana na prihvaćenim trenažnim uputstvima. •Agenti za pronalaženje informacija. Softverski agenti mogu biti poslati da traže i da dostavljaju, donose informacije, npr. sa Interneta. Agenti sadrže znanje o korisnikovim preferencijama i potrebama, i mogu takođe da imaju i znanje iz sporta, kako bi bili u mogućnosti da procene važnost i korisnost onoga {to su na{li. •Prepoznavanje i interpretacija slika. Mnoge slike u obliku krivulja (npr. pulsnog opterećenja) mogu da budu automatski interpretirane, od standardnih do kompleksnijih slika. Podaci o sportisti su ulazi, a izlazi su dijagnoza – preporučeni trenažni metodi, sredstva i opterećenja na treningu. Es nisu kreirani sa namerom da potpuno zamene stručna lica, trenere, već kao velika ispomoć. Tako funkcioni{e npr. Omega vejv (OW) sportsko tehnolo{ki sistem (Omega Wave Sport Technology System). Ovaj sistem vr{i dijagnozu jednog sportiste/tima u vezi telesnog i psihičkog opterećenja radi optimalizacije trenažnog procesa. OW analizira električnu aktivnost u srcu i sporim moždanim talasima, da bi stvorio „unutra{nju sliku“ kako telo sportiste funckioni{e. Pri tome, OW to čini brzo, nestresno i ne-invazivno. Po prvi put ikada, sportisti, treneri, fiziolozi i naučnici mogu da nadgledaju (monitor) cikluse stresa i oporavka svojih sportista na dnevnoj bazi. Sa OW, danas je moguće pratiti, kod svakog sportiste, njegovu adaptaciju na zahteve treninga, takmičenja, putovanja i ostale stresove. Putem 25 INTRODUCTORY LECTURE UVODNO PREDAVANJE Stefanović, \.: SPORTS AND ARTIFICIAL INTELLIGENCE Proceedings 2010, 22-33 for each sportsman, his adaptation to requirements of training, matches, travels and other stressful situations. A proper managing of stressful and recovery cycles allow coaches to train the adaptive response from a player, so that he/she adapts much faster than before. In this way, OW correlates the sports science/theory with sports practice. Lately, the application of computer systems in a sport training is more and more present. Can a computer (ES) replace a coach in managing the system of sport preparation? There are fitness centres where its member can simply enter into a computer what he/she wants to achieve, and then it makes the plan and program for him/her. As the member goes through various machines (stations), the computer adjusts the plan and program to the member’s reactions. What if, someday, achievements in Information Technologies would be so high that we could create a single ES which would be homomorphous (of the same shape), analogue, even isomorph (similar) to a coach? Could it guide a sportsman to the final success/results at a competition? In order to develop such ES, we should find an algorithm (a series of individually interconnected procedures resulting in a solution of a problem) which would provide for a coach to manage the system of preparation of sportsmen. Thereat, the plan and program, and any corrections thereto, are just the result of such algorithm, which is aimed to that the desired condition is achieved, set by a model. This is primarily the matter of determinism (the determinism being here perceived as a pre-known behaviour of a system, conditioned by its current state), which can be applied to lifestyle and not only to a sports training. Is a man’s consciousness (awareness) just one complex algorithm? We firmly believe that it is not, otherwise there would be no free will. This has direct implications to the issue man against machine in managing training. How a machine can be constructive, creative minded? A machine can learn, adapt, but it can never be an artist (inventive creator) and have free will like a sports coach. We should keep in mind that managing a system of sports preparation is the art, in its large part, as well as the science is. A machine can never be an artist. dobrog upravljanja stresnih i oporavljajućih ciklusa, moguće je trenirati adaptivni odgovor sportiste, tako da se on/ona adaptira mnogo brže nego pre. Na taj način OW povezuje nauku/teoriju sporta sa sportskom praksom. U poslednje vreme prisutna je sve veća primena računarskih sistema u sportskom treningu. Može li računar (Es) da zameni trenera u upravljanju sistemom sportske pripreme? U nekim fitnes klubovima, član jednostavno u računar unese {ta želi da postigne, a zatim mu on pravi plan i program. Kako član prolazi kroz razne ma{ine (stanice), tako računar koriguje plan i program prema reakciji člana. Šta ako bi jednog dana, dostignuća u informatičkoj tehnologiji bila tako visoka da se kreira jedan Es koji bi bio homomorfan (istog oblika), analogan, pa čak izomorfan (sličan) treneru? Da li bi on mogao bolje da vodi sportistu do konačnog uspeha/rezultata na takmičenju? Da bi se napravio jedan takav Es, morao bi da se pronađe algoritam (niz pojedinačno povezanih postupaka koji dovode do re{enja nekog problema) kojim trener upravlja sistemom pripreme sportista. Pri tome su plan i program, kao i njihovo korigovanje, samo rezultat tog algoritma, koji ima za cilj da dostigne željeno stanje postavljeno od strane modela. Ovo je pre svega stvar determinizma (ovde se determinizam shvata kao unapred poznato pona{anje nekog sistema koje je uslovljeno njegovim trenutnim stanjem), koji može da se primeni i na život sam, a ne samo na sportski trening. Da li je čovekova svest samo jedan kompleksan algoritam? Mi čvrsto držimo da nije, jer onda ne bi postojala slobodna volja. Ovo ima direktne implikacije na problem čovek protiv ma{ine u upravljanju treningom. Kako ma{ina može da bude kreativna, da ima stvaralački duh? Ma{ina može da uči, da se adaptira, ali nikad neće moći da bude umetnik (kreativni stvaralac) i da ima slobodnu volju kao sportski trener. Mora se zapamtiti da je upravljanje sistemom sportske pripreme u jednom dobrom delu umetnost, kao {to je i nauka. A ma{ina nikad ne može da bude umetnik. Electronic Games Elektronske igre (Ei) predstavljaju igre kod kojih se koristi elektronika u cilju formiranja interaktivnog sistema sa kojim se igra. Danas je najprisutnija forma elektronskih igara u obliku video igre (Vig) – Ei koje se baziraju na interakciji sa igračem putem korisničkog interfejsa i formiranju odgovora na video uređajima. Prema postojećim klasifikacijama postoji preko dvadesetak različitih vrsta Vig od kojih su najpoznatije: arkadne igre, avanturističke, borilačke, simulacije, edukativne igre i za nas relevantne sportske igre. Sportske video igre (SVig) su video igre koje simuliraju tradicionalne sportove. Najveći broj sportova danas poseduje i svoju elektronsku varijantu, bilo da se radi o timskim sportovima, atletici, ili ekstremnim sportovima. SVig predstavljaju psihofizičke i taktičke izazove za igrača i stavljaju na proveru njegovu preciznost i tačnost. One su uglavnom bazirane prema složenim modelima kretnih aktivnosti aktuelne grane/discipline sporta, uključujući brzinu, snagu, ubrzanje, preciznost pa čak i izdržljivost. Igre su sme{tene u virtualni svet sličan onom iz stvarnog života: igraju se u okruženju stadiona, sportskih dvorana, ili na otvorenom prostoru. Modeli SVig su veoma verno razvijeni tako da se sa uspehom mogu koristiti za inicijalno obrazovanje, ili obnavljanje znanja vezanog za pravila same igre. Igre mogu da obuhvataju jedan-na-jedan interakciju sa virtuelnim protivnikom, strategiju izbora i pripreme u slučaju igara Electronic games (EG) are games which employ electronics to create an interactive system with which a player can play. The most common form of electronic game today is the video game (Vig) – EG based on the interaction with a player using a user interface to generate feedback on video devices. According to the existing classifications there are over twenty different types of Vig, where the most popular are: arcade games, adventure games, fighting games, simulation games, educational games and, the most relevant for us, sports games. Sports Video Games (SVig) are video games that simulate the playing of traditional sports. Most sports have today their electronic variant, including team sports, athletics and extreme sports. SVig involve physical and tactical challenges for a player, and test his/her precision and accuracy. The games are mostly based on models of motion activities and actual sports branch/discipline, including speed, strength, acceleration, accuracy and even endurance. The games are placed in the virtual world similar to the real one: they take place in a stadium, arena or outdoors. SVig models are very realistically developed so that they can be successfully used for the initial education or for recapitulation of the knowledge related to the rules of that specific gameplay. Games can 26 Elektronske igre Zbornik radova 2010, 22-33 include one-on-one interaction with a virtual rival, strategy vezanih za timske sportove, ili simulacije stvarnih situacija of selection and preparation in case of games related to u sportu i oko sporta. team sports, or simulation of real situations in sports and Kompanija Nintendo je 2006. izdala Vi sport kolekciju – Vsk related to sports. (Wii Sports colection) SVig za Vi (Wii) konzolu. Na ovoj In 2006, the company Nintendo released Wii Sports Col- platformi igrač mora fizički da pokreće svoj daljinski upravljač lection – WSC for the Wii console. On this platform a player kako bi simulirao pokret svog avatara (virtuelnog alter ega has to move physically its remote control in order to simu- samog igrača). Ovim je svet video igara polako iz svere silate the movement of his avatar (virtual alter ego of the mulacije evoluirao ka emulaciji sveta sportske igre. Vsk player). In this way, the world of video games slowly evolved poseduje mogućnost igranja pet različitih sportova: boksa, from the area of simulation towards emulation of sports kuglanja, golfa, tenisa i bejzbola. U toku igre, igrač (sportista) games. WSC has the possibility of playing five different sports: prati progres razvoja svojih ve�������������������������������� {������������������������������� tina i koristi treninge na razboxing, bowling, golf, tennis and baseball. In the course of ličitim nivoima razvoja. the game, a player (sportsman) follows the progress of the Iza uspeha sa Vsk Nintendo je 2008. izdao i Vi fit (Wii Fit) development of his/her skills and makes benefit of trainings koji pruža mogućnost vežbanja aerobika i rekreativnih vežon different levels of the development. bi. Poseduje namenski razvijenu balans platformu (Wii BaAfter the success of WSC, Nintendo also released Wii Fit in lance Bord) preko koje je obezbeđena jo{ neposrednija 2008, which gives aerobic and recreation exercises. It has a interakcija igrača – sada već rekreativnog sportiste i platforspecially developed balance platform (Wii Balance Board) me. which allows a more indirect interaction between a player Slika 5: Kibernetički model upravljanja pripremom sportista bez sportskog trenera Figure 5: Cybernetic model of managing the preparation of sportsmen without a coach – now of a recreational sportsman - and the platform. Neural Networks Neural networks (NN) can be defined as the manner in which the nervous system in humans is organized. In a wider sense, they represent the potential for modeling a synthetic (computer) network by utilizing the principles of organization of a human neural network. At the lowest level of complexity, NN serve as an intermediary between the somatosensory and motor system of an organism going in both directions. If we look at the physiological processes of creating an impulse in the sensory system as a whole, we will see that all the mechanisms involved in those processes are basically of electromagnetic nature, for they serve to cause the signal to be above the activating threshold of a neuron. In order for these issues to be understood and properly investigated, it is necessary to acquire the knowledge about the relevant space of bioelectric activity of a neuron or a larger cluster of neurons, pertaining to: •different kinds of sense receptors and the manner of their activation, •the generation and spread of a nerve impulse, Neuronske mreže Neuronske mreže (Nm) predstavljaju način organizacije nervnog sistema kod čoveka. [ire značenje predstavlja mogućnost modelovanja sintetičke (kompjuterske) mreže kori{ćenjenjem principa organizacije ljudske neuronske mreže. Na najjednostavnijem nivou složenosti, Nm služe kao posrednik između somatosenzornog i motoričkog sistema organizma u oba smera. Ukoliko se globalno posmatraju fizički procesi nastanka impulsa u senzornom sistemu, uočavamo da su svi mehanizmi pri tim procesima u osnovi elektromagnetne prirode, jer isti treba da uzrokuju signal iznad akcionog praga neurona. Da bi se ova problematika razumela i pravilno proučavala neophodno je razumeti relevantni prostor bioelektrične aktivnosti jednog ili veće grupe neurona koji se odnosi na: •vrste čulnih receptora i način njihove aktivacije, •generisanje i prostiranje nervnog impulsa, •pasivni i aktivni membranski transport jona (Na+, K+, Cl–), 27 INTRODUCTORY LECTURE UVODNO PREDAVANJE Stefanović, \.: SPORT I VE[TAČKA INTELIGENCIJA INTRODUCTORY LECTURE UVODNO PREDAVANJE Stefanović, \.: SPORTS AND ARTIFICIAL INTELLIGENCE Proceedings 2010, 22-33 •passive and active membrane transport of ion (Na+, K+, Cl–), •electrical activities in the brain (electroencephalograph, EEG) and •magnetic activities in the brain (magnetoencephalograph, MEG). •moždane električne aktivnosti (elektroencefalogram, EEG) i •moždane magnetne aktivnosti (magnetoencefalogram, MEG). The analysis of bioelectric signals themselves makes use of gamma-function mathematical transformations (from simpler to very complex ones). The electrical activities in the brain at the level of NN as well as the ones related to the brain waves are also relevant to various psychological functions, such as: recognition, memorizing, learning, thinking, creativity, consciousness, language faculties, etc. What is the nature of the interaction between an organism and the environment? Biological systems (organisms) constantly interact with their environment. They continuously exchange matter and energy with it. This openness of biological systems enables biological development. However, the organisms interact with the environment by means of the senses, through which they constantly receive new information in different forms, which are further converted into nerve impulses. The nerve impulses are then processed in hierarchical neural networks CNS, where they are interpreted also as more complex psychological experiences. The input of information into the nervous system is enabled by sense receptors, which register sensory stimuli, such as touch, pain, cold, heat, sound, light, taste, smell, etc. Receptors turn sensory stimuli into nerve impulses – basic mechanisms of conversion. All sense receptors have one feature in common – receptor potential. The immediate impact of any specific stimulus activating the receptor is manifested as a change in potential on the receptor membrane. When the receptor potential rises above critical level in the nerve fibre attached to the receptor, it results in the creation of action potential. In this process, the more the receptor potential rises above the threshold of action potential, the higher the frequency of action potential, which is one of the factors influencing the experience of intensity of a sensory stimulus in the brain. The other factor is the number of activated receptors above the threshold, which is determined by the number of sensory nerve fibers transmitting nerve impulses into the primary sensory zone of the cortex. A case from practice It is important for a sportsman or a sportswoman to possess highly developed proprioceptive abilities. The manner in which a human organism perceives shapes is perfectly exploited by the great masters of martial arts (e.g. dr Masaaki Hacumi from Japan, the head of the organization Bujinkan or Morihej Ueshiba, the founder of Aikido), but it is very poorly investigated in scientific circles. It is very unusual that they manage to overcome several adversaries at a time simultaneously and in a relatively short space of time, while their movements seem much slower than the reasonably expected maximum (Figure 6). One of the most demanding defense scenarios among all “one on one” systems in the Far Eastern tradition of martial arts is the bare-handed defense from an assailant armed with a samurai sabre. Analytically speaking, without going into detail concerning the nature of the skill, chances of “mere” survival are measured in terms of thousandths, i.e. they are certainly close to zero even if they come up against a barely adept swordsman. In the practice of the great masters the chances are significantly higher. Namely, according to the tennets of proprioceptive abilities of a human organism, the slightly surprising order in 28 Analiza samih bioelektričnih signala raspolaže gamom matematičkih transformacija (od jednostavnijih do veoma robustnih). Moždane električne aktivnosti na nivou NM i moždanih talasa značajne su i za psiholo{ke funkcije: prepoznavanje, memorisanje, učenje, mi{ljenje, kreativnost, svest, reči... Kako izgleda interakcija organizma i okoline? Biolo{ki sistemi (organizmi) nalaze se u neprekidnoj interakciji sa okolinom. Oni sa njom neprekidno razmenjuju materiju i energiju. Zbog ove otvorenosti biolo{kih sistema omogućen je i biolo{ki razvoj. Međutim, organizmi sa okolinom su u interakciji posredstvom čula, preko kojih neprekidno dobijaju informacije u različitoj formi, koje se dalje konvertuju u nervne impulse. Ti nervni impulsi se potom obrađuju u hijerarhijskim neuronskim mrežama CNS gde se interpretiraju i u složenije psiholo{ke doživljaje. Ulaz informacija u nervni sistem omogućavaju čulni receptori, koji registruju čulne draži, kao {to su dodir, bol, hladnoća, toplota, zvuk, svetlost, ukus, miris itd. Receptori pretvaraju čulne draži u nervne impulse – osnovni mehanizmi konverzije. Svi čulni receptori imaju jedno zajedničko obeležje – receptorski potencijal. Neposredni učinak bilo koje specifične draži koja pobuđuje receptor se manifestuje u obliku promene potencijala na receptorskoj membrani. Kada receptorski potencijal poraste iznad praga akcionog potencijala u nervnom vlaknu priključenom receptoru, počinje pojava akcionih potencijala. Pri tome, učestalost akcionih potencijala utoliko je vi{a, ukoliko receptorski potencijal vi{e nadma{uje nivo praga akcionog potencijala, {to je jedan od faktora koji utiču na doživljaj intenziteta čulne draži u mozgu. Drugi je broj pobuđenih receptora iznad praga, {to određuje broj senzornih nervnih vlakana koji prenose nervne impulse u primarne senzorne zone korteksa. Slučaj iz prakse U sportu je bitno da sportista poseduje na vrlo visokom nivou propriocepcijske sposobnosti. Način na koji ljudski organizam opaža oblike praktično je savr{eno iskori{ćen od strane vrhunskih majstora borilačkih ve{tina (npr. dr Masaaki Hacumi iz Japana, poglavar organizacije Buđinkan ili Morihej Ue��������������������������������������������� {�������������������������������������������� iba, osnivač aikidoa) je veoma malo istraživan u naučnim krugovima. Veoma je čudno {to oni uspevaju da savladaju i po nekoliko protivnika simultano u relativno kratkom vremenskom intervalu, dok im pokreti izgledaju prilično sporiji od realno očekivanog maksimuma (Slika 6). Jedan od najtežih scenarija za odbranu u svim sistemima „jedan na jedan“ u tradiciji istočnjačkih borilačkih ve������������������������������������������������ {����������������������������������������������� tina je odbrana golim rukama od napadača naoružanog samurajskom sabljom. Analitički gledano, bez detaljnijeg ulaženja u prirodu ve{tine, {anse za „puko“ preživljavanje se mere promilima, tj. svakako su veoma blizu nuli ukoliko je „preko puta“ iole ve{t mačevalac. U praksi vrhunskih majstora ova verovatnoća značajno raste. Naime, prema postulatima propriocepcijskih sposobnosti ljudskog organizma, redosled zapažanja parametara objekata se kreće pomalo neočekivanim redosledom u tri faze: I faza – pomeranje objekta, II faza – oblik objekta i which the parameters of an object are perceived includes three phases: the first phase – the change of location of an object; the second phase – the shape of an object; and the third phase – the colour and relief of an object. In connection with that, we should note the common fact that the objects that are moving faster are more quickly observed than the slower ones. In order to trick the assailant, a master makes rather slow moves, always keeping his silhouette unchanged in the eyes of the assailant, and by constant movement reaching a more favourable distance (surely a shorter one in this scenario). Such concept is sometimes used unawares by top dribblers/defense players in collective sports and thus deserves a much deeper analysis as well as a wider application. One illustrative example is the dribbling of Dejan Bodiroga – it was always met with controversial comments, pointing out that he “was not fast enough, but somehow he Zbornik radova 2010, 22-33 III faza – boja i reljef objekta. S tim u vezi, važi napomena da objekti koji se brže kreću bivaju pre uočeni od sporijih. Da bi prevario napadača, majstor pravi pokrete koji su prilično spori, permanentno održavajući svoju siluetu neizmenjenu u očima napadača, svojim stalnim kretanjem dostižući povoljniju distancu (svakako kraću pri ovom scenariju). Ovaj koncept je ponekad nesvesno iskori{ćen od strane vrhunskih driblera/odbrambenih igrača u kolektivnim sportovima i zaslužuje znatno detaljniju analizu i {iru primenu. Jedan od tih primera je dribling Dejana Bodiroge – uvek je postojao kontroverzni komentar da on „nije dovoljno brz, ali da nekako uvek prođe“, {to ga je naravno dovelo u rang najboljeg duel igrača svoga vremena. Slika 6: Primena propriocepcijskih sposobnosti kod samurajske tehnike Figure 6: The application of proprioceptive abilities in the samurai techniques always manages to get through”, which naturally put him in the rank of one of the best opposition players of the time. How does the body move from the standpoint of spacial efficacy of a motor neuron? Generation of a motor signal comes from the direction of the cortex, goes down along the spinal cord, depending on which cluster of motor neurons is responsible for the innervation of corresponding muscle fibres. Since the transmission speed of nerve impulses is limited, it is obvious that the time of propagation of a nerve impulse from the cerebral cortex to the activating neuron is in direct proportion to the distance of motor end plate from the corresponding spinal vertebra. This parameter is greatly important for the cultivation of fast movements. By regular body training one should become accustomed to activating the muscular structure along the spinal cord at the motor end plate of the furthest innervating neuron when making any kind of complex movement. For instance, if in volley-ball a player wants to hit the ball from the initial position with his hands down, he will first innervate the muscles for lifting the shoulders, then the upper arms, followed by the forearms, and only lastly those of the hands and fingers (of course, an adequate reaction of the leg muscles is taken for granted, but again applying the same principle – moving from the region of the hip downwards). Apart from minimizing the time for appropriate reaction, adhering to this principle allows for subsequent adjustements if the situation changes abruptly. In the above-mentioned example, if Kako se izvodi pokret sa stanovi{ta prostorne efikasnosti motoričkog neurona? Generisanje motoričkog signala kreće se iz pravca korteksa niz kičmeni stub u zavisnosti koja grupa motoričkih neurona je određena za invervaciju odgovarajućih mi{ićnih vlakana. Po{to je brzina prostiranja nervnih impulsa ograničena, očigledno je da je vreme propagacije nervnog impulsa od kore velikog mozga do aktivacionog neurona proporcionalna udaljenosti kraja inervacionog neurona od odgovarajućeg kičmenog pr{ljena. Ovaj parametar je od izuzetnog značaja za kultivisanje brzih pokreta. Kroz redovan telesni trening trebalo bi stvarati naviku da se pri svakom složenom pokretu aktiviraju mi{ićne strukture uz samu kičmu ka kraju najdaljeg invervacionog neurona. Npr. ukoliko u odbojci igrač želi smečovati loptu iz početnog položaja spu����������������������������������� {���������������������������������� tenih ruku, on će najpre inervirati mi{iće za podizanje ramena, potom nadlaktice, zatim podlaktice i tek na kraju {ake i prstiju (naravno, adekvatna reakcija mi{ića nogu se podrazumeva, ali uz po{tovanje istog principa – krećući se od oblasti kuka pa nadole). Pored minimizovanja vremena pravilne reakcije, po{tovanjem ovog principa ostavlja se mogućnost naknadnog prilagođavanja ukoliko se situacija naglo promeni. U gore pomenutom primeru ukoliko je lopta npr. okrznula vrh mreže, organizam nije jo{ uvek napravio fine pokrete 29 INTRODUCTORY LECTURE UVODNO PREDAVANJE Stefanović, \.: SPORT I VE[TAČKA INTELIGENCIJA INTRODUCTORY LECTURE UVODNO PREDAVANJE Stefanović, \.: SPORTS AND ARTIFICIAL INTELLIGENCE Proceedings 2010, 22-33 the ball happened to make contact with the top part of the net, the organism still had not made fine movements of the fingers, the hand and maybe even the forearm, but only that of the shoulders, for example, so the potential for correction of movements is optimal. prstiju, {aka i možda podlaktice, već samo npr. ramenskog dela, tako da je mogućnost za korekciju pokreta maksimalizovana. Ovaj princip je opravdan i sa stanovi��������������������� {�������������������� ta energetske efikasnosti, {to u slučaju dugih i iscrpljujućih mečeva predstavlja presudan faktor. Naime, ovim se izbegavaju brojne „preterane“ reakcije spoljnih delova ekstremiteta. Golman u fudbalu npr. pomera najpre ramena pripremajući se za potencijalnu reakciju. U sledećem trenutku njegov čulni sistem opaža da dalji pokret nije neophodan, jer lopta ide preko gola. Pomeranje ostalih mi��������������������������� {�������������������������� ića ruku nije vi���������� {��������� e neophodno. Ukoliko bi se invervirala celokupna ruka, ta bi energija bila uzaludno potro{ena. U čemu se ogleda su{tina moždane hijerarhijske neuronske mreže i kognitivne implikacije? Danas preovlađujuća naučna paradigma jeste da se procesiranje informacija na nivou CNS odigrava posredstvom hijerarhijski organizovanih i povezanih neuronskih mreža. Npr. vizuelna informacija prvo se hijerarhijski procesira na nivou mrežnjače (počev od mreže fotoreceptornih čepića i {tapića, pa do mreže ganglijskih ćelija), da bi se hijerarhijsko procesiranje nastavilo na nivou primarnih, sekundarnih i tercijarnih senzornih, ili interpretacijskih područja u kori velikog mozga (od kojih se svako sastoji od hijerarhije nekoliko neuronskih mreža). Veze unutar kao i između susednih neuronskih mreža u ovoj hijerarhiji ostvaruju se posredstvom sinapsi (jedan neuron može da ostvari oko 40.000 sinaptičkih veza sa susedima), koje mogu biti eksitatorne ili inhibitorne. Osim toga, tokom procesa učenja značajnu ulogu u globalnoj distribuciji (po celoj moždanoj kori) hijerarhijski obrađivanih informacija igraju i moždani talasi. Sekvencijalni (fon Nojmanovi) računari danas imaju takt ~ 10-10 s, dok je prosečno vreme generisanja akcionog potencijala neurona ~ 10-3 s. Iako je ovaj odnos brzine aktivacije pojedinačnih procesirajućih elemenata ~ 107 puta veći kod sekvencijalnih poluprovodničkih računara, ipak je mozak superioran nad njima kada se radi o nekim komplikovanim zadacima, kao {������������������������ ������������������������� to su obrada i prepoznavanje slike, orijentacija i kretanje u prostoru promenljivih karakteristika, razumevanje govora itd. Razlog velikih mogućnosti mozga leži u paralelnoj obradi informacija. Osim toga, po{to je broj neurona u mozgu, kao i broj veza između njih konstantan, znanje je distribuirano po vezama, a nove informacije se dodaju pode{avanjem jačine veza između neurona. Takođe, određeni delovi informacija se ne nalaze na tačno određenim pozicijama, nego su distribuirani po regionima u mozgu. Time o{tećenje neurona, pa čak i grupa neurona, ne utiče u većoj meri na pogor��������������������������������������������� {�������������������������������������������� anje performansi sistema, dok kod većine sekvencijalnih računara uni{tenje dela procesorske jedinice, ili dela memorije vodi, ili ka prestanku rada celog sistema, ili do nepovratnog gubitka informacija. Za razliku od sekvencijalnih računara, kod kojih centralna procesorska jedinica kontroli{e sve interne aktivnosti i ima pristup memoriji, kod mozga je upravljanje lokalno. Pona{anje svakog neurona u mozgu zavisi samo od njegovog prethodnog znanja i od ulaznog okruženja, pa se može reći da je izlaz svakog neurona funkcija lokalno dostupne informacije. This principle is also justified from the viewpoint of energy efficiency, which in the case of prolonged and exhausting matches represents a crucial factor. Namely, in this way numerous overreactions of external parts of the extremities are avoided. For example, the goalkeeper in football moves his shoulders first when he’s preparing himself for a potential reaction. In the next moment, his sensory system perceives that further movement is unnecessary, because the ball misses the goal. Activating other arm muscles is no longer necessary. If the whole arm had been innervated, it would mean energy wasted. What is the essence of hierarchical neural networks in the brain as well as of cognitive implication? Nowadays, the predominant scientific paradigm assumes that information processing at the level of CNS takes place among hierarchically organized and interconnected neural networks. For instance, a piece of visual information is firstly processed at the level of retina (beginning with a network of photoreceptive plugs and sticks, and ending with a network of ganglion cells), and the hierarchical processing continues at the level of primary, secondary and tertiary sensory or interpretative regions in the cerebral cortex (each of which consists of a hierarchy of several neural networks). Connections inside one as well as between neighbouring neural networks in this hierarchy are realized by means of synapses (one neuron can realize about 40,000 synaptic connections with its neighbours), which can be excitatory or inhibitory. Apart from that, in the learning process a significant role in the global distribution (all over the cortex) of hierarchically processed information is played by brain waves. Sequential (von Neuman’s) computers now have a tact ~ 10-10 s, whereas an average time of generating action potential in a neuron is ~ 10-3 s. Although this proportion between the speed of activation of particular processing elements is ~ 107 times greater in sequential semi-conducting computers, the brain is still superior to them when it comes to some complex tasks, such as image processing and recognition, orientation and movement in space having changeable features, speech recognition, etc. The reason for such great capabilities of the brain lies in parallel information processing. Besides, as the number of neurons in the brain, as well as the number of connections between them is constant, knowledge is distributed along the connections, and new information is added by adjusting the strength of connections between neurons. Furthermore, certain parts of information are not placed in specific positions, but are distributed in different regions of the brain. Thus, possible damage in neurons, and even in a cluster of neurons, does not greatly affect the system’s performance, while in the majority of sequential computers the destruction of a part of a processor unit or a part of its memory leads either to the whole system shutting down or to an irretrievable loss of information. Unlike sequential computers, in which a central processor unit controls all internal activities and is able to access the memory, the brain is locally controlled. The behaviour of each neuron in the brain depends solely on its prior knowledge and of the input environment, so we can conclude that the output of each neuron is a function of locally available information. NN as an attempt at modelling the workings of the human brain have the following positive traits: parallel processing, 30 NM kao poku{aj modeliranja rada ljudskog mozga imaju sledeća dobra svojstva: paralelan rad, izvr{enje komplikovanih zadataka u relativno kratkom vremenu, distribuiranu raspodelu informacija, slabu osetljivost na o{tećenja, kao i Zbornik radova 2010, 22-33 execution of complex tasks in a relatively short space of time, distribution of information, low sensitivity to damage, as well as the learning ability, that is, the ability to adapt itself to changes in the environment and improve its functioning based on experience. The advantage of the architecture of hierarchical NN is that functionally specialized neurons in each layer process only a limited amount of information. mogućnost učenja, odnosno adaptacije na promene u okruženju i pobolj��������������������������������������������� {�������������������������������������������� anje rada na osnovu iskustva. Prednost arhitekture hijerarhijskih NM je da funkcionalno specijalizovani neuroni svakog sloja procesiraju samo ograničenu količinu informacija. Software agents Kompjuterska nauka defini{e softverske agente kao delove softvera koji rade za račun korisnika ili druge softverske aplikacije u saradnji sa agencijom. Agencija u ovom slučaju predstavlja, najče����������������������������������������� {���������������������������������������� će Es koji odlučuje o akcijama i adekvatnosti akcija agenata. Agenti kao softverske komponente imaju visok nivo samostalnosti, aktiviraju se i deluju samostalno, a ne pod uticajem drugih aplikacija. Izvedeni koncept softverskog agenta predstavljaju inteligentni agenti koji poseduju karakteristike i sposobnosti Vi, odnosno učenja i zaključivanja. Smatra se da danas postoje samo četiri tipa inteligentnih softverskih agenata: Computer science defines software agents as parts of software that work for the sake of the user or another software application in cooperation with an agency. The agency in this case is mostly an ES which decides on actions and the adequacy of the agent’s actions. The agents as software components have a high degree of autonomy, they are activated and operated independently, and are not controlled by other applications. Such concept of a software agent uses intelligent agents that possess the characteristics and functions of AI, or learning and inferring. It is thought that today there are as many as four types of intelligent software agents: •Agents for purchase on electronic stalls travel across the network accumulating information about goods and services on offer. These agents work very effectively at the sales of electronic goods and services, and Amazon.com is the best example of a successfully implemented technology of this type of agent. This web site can offer you a list of books or music based on your current or prior purchases. •Personal agents are intelligent agents that work on your behalf. •Monitoring-proactive agents are used in complex computer systems for monitoring and reporting on the state of equipment. These agents also control stocks of spare parts for the equipment, prices of new parts or new pieces of equipment, and then they forward the information to its users. •Data-mining agents use information technologies in order to discover the rules and patterns in a wealth of information coming from a great variety of sources, and thereby narrow the set of sources important for the users themselves. A case from practice... There are many ways to perform an analysis of sportspeople’s activities concerning their competition. In order for these matters to be understood, we are going to give an account of one case from volley-ball practice. „Data Volley 2“ (DV-2), is the only scout programme for volley-ball used by the best teams in Italian Championship, as well as all the best national teams in the world. Like other „company’s diamonds“, this programme is available in several versions adaptable to every level. Why DV-2? DV-2 is the most popular and the most widely used statistical scout software in the world. All the bigger clubs and national teams in the world chose DV-2 as their only instrument for scouting and analysis of team statistical data because it was assessed to be extremely professional and comprehensive. DV-2 is Data project’s response to the coaches’ request for complete and detailed results in a very short time interval. Features of DV-2 Extreme comprehensiveness: DV-2, a programme adopted by the best national and club teams all over the world is the Softverski agenti •Agenti za kupovinu na elektronskim tezgama putuju mrežom dopremajući informacije o ponuđenoj robi i servisima. Ovi agenti rade veoma efikasno na prodaji elektronske robe i servisa, a Amazon.com je najbolji primer uspe������������������������������������������������ {����������������������������������������������� no implementirane tehnologije ovakvog tipa agenata. Ovaj veb sajt će vam ponuditi listu knjiga ili muzike na osnovu va{e tekuće i va{ih predhodnih kupovina. •Personalni agenti su inteligentni agenti koji deluju u va{e ime. •Monitoring-proaktivni agenti se koriste u kompleksnim računarskim sitemima za nadgledanje i izve{tavanje o stanju opreme. Ovi agenti prate i stok rezervnih delova za opremu, cene nabavke novih delova ili opreme i ove informacije prosleđuju korisnicima. •Dejta majning agenti koriste informacione tehnologije kako bi na{li pravila i obrasce u obilju informacija koje potiču od velikog broja raznorodnih izvora i na taj način suzili skup značajnih izvora za samog korisnika. Slučaj iz prakse... Postoji ne mali broj načina za analizu takmičarske aktivnosti sportiste. Da bi se razumela navedena problematika objasniće se slučaj iz odbojka{ke prakse. „Data volej 2“ (DV-2), (engl. „Data Volley 2“), je jedini skautski program za odbojku koji koriste najbolji timovi u italijanskom ����������������������������������������������� {���������������������������������������������� ampionatu, kao i svi nacionalni najbolji timovi na svetu. Kao svaki „dijamant kompanije“, program je dostupan u vi{e verzija koje su prilagodljive svim nivoima. Za{to DV-2? DV-2 je najpoznatiji i najkori{ćeniji statistički skautski softver na svetu. Svi veći klubovi i nacionalni timovi na svetu izabrali su DV-2 kao svoj jedini instrument za skautizam i analizu timskih statističkih podataka zbog njegovog procenjenog nivoa profesionalizma i sveobuhvatnosti. DV-2 je odgovor Data projekta na zahtev trenera o kompletnim i detaljnim rezultatima u kratkom vremenskom intervalu. Mogućnosti DV-2 Ekstremna sveobuhvatnost: DV-2, program usvojen od strane najboljih nacionalnih i klupskih timova sveta jedini je statistički skautski softver koji omogućava korisniku da odmah 31 INTRODUCTORY LECTURE UVODNO PREDAVANJE Stefanović, \.: SPORT I VE[TAČKA INTELIGENCIJA INTRODUCTORY LECTURE UVODNO PREDAVANJE Stefanović, \.: SPORTS AND ARTIFICIAL INTELLIGENCE Proceedings 2010, 22-33 only statistical scout software which enables the user to immediately get extremely reliable data easily presentable on the screen, which is greatly helpful for the coach in his decision-making during the match. Comprehensive version: DV-2 is available in two versions to better meet different needs. Basic version: it gives a wide range of options for scouting and analysis at a very favourable price. With this version of the programme you can get a visualized statistics for each player, team, rotation, skill, as well as a graphic display of the action zone as the direction of an attack. Professional version: The software is amenable to an infinite number of possibilities for personalization of required information during defining the parameters in phases, ranging from the choice of discipline to be monitored and at which level to the visualization of the direction of an attack. Speaker possibilities for development: It is possible to connect another computer on the bench to the scout’s one, allowing those on the side to see the data directly during the match. Also, it is possible to connect DV-2 score-board to an interactive screen. It is placed in front of the audience as an entertaining and commercial promotion using visualization of statistical data going live during matches. Programme architecture: The philosophy/architecture that characterizes DV-2, making it the most widely used statistical scout programme in the world, is based on its enormous conformity to all user capabilities and needs: from national trainers to beginners, everybody finds that with DV-2 they are able to scout and analyze whatever they need during a volley-ball match. Flexibility: Programme functions can be personalized, so that they are adjusted to personal capacities of the user: from keyboard responsiveness to evaluation table of skills, from compiling the criteria to printing out statistical reports. Controlled scouting: The analysis of field zone in which the skills are played out – for each analysis it is possible to visualize four different values to help the coach and different skills so he could quickly identify parts of the field where the best and the worst moves are performed. Analysis of directions: It shows the direction of the serve and the attack. It is possible to require an overall or detailed analysis either of the team or of the individual players under certain circumstances. DV-2 uses different colours to mark the best, the worst and the mediocre moves. Work base: It replaces real volley-ball floor surface and enables the user to study all the statistical data of scout matches. To this end, there is a possibility of personalizing prospects of analysis based on personal needs by inputing very complex formula. Direction of the attack: It detects the efficacy and the direction of attacks depending on the region of the attack, the quality of the impact, etc. Details of the last score: The video screen shows the last score for each player, and each of their skills following the „trend“ of checking up on every player in every technical aspect. HTLM match report: A statistical overview of the match is created in HTLM format for the purpose of publishing it on the club’s web site or of forwarding it to other users via the network. usvoji ekstremno pouzdane podatke lake za prikazivanje koji mogu pomoći treneru u dono{enju odluke tokom meča. Sveobuhvatna verzija: DV-2 je dostupan u dve verzije radi boljeg prilagođavanja različitim potrebama. Osnovna verzija: Daje {irok spektar mogućnosti skautinga i analiza po pristupačnoj ceni. Sa ovom verzijom programa moguća je vizuelizacija statistika za svakog igrača, tim, rotaciju, ve{tinu, i grafički prikaz zone akcije kao pravca napada. Profesionalna verzija: Softver pristaje na beskonačno mnogo mogućnosti za personalizaciju željenih informacija tokom definicija u fazama parametara, od izbora koja ve{tina se skautuje (bira) i na kom nivou, do vizuelizacije pravca napada. Spiker mogućnosti za razvoj: Moguće je povezati drugi kompujer na klupi za skautov, dozvoljavajući onima sa strane da konsultuju podatke direktno tokom meča. Moguće je povezati DV-2 bodovnu tabelu na interaktivni ekran. On se nalazi ispred publike kao zabavna i komercijalna promocija sa kori{ćenjem vizualizacije statističkih podataka uživo tokom mečeva. Programska arhitektura: Filosofija/arhitektura koja karakteri{e DV-2, čineći ga najra���������������������������������������� {��������������������������������������� irenijim i kori������������������������ {����������������������� ćenim statističkim skauting programom na svetu, je njegova kompletna dostupnost svakim korisničkim sposobnostima i potrebama: od nacionalnog trenera do početnika, svi nalaze da sa DV-2 imaju mogućnosti skautinga i analize svega {to je potrebno tokom odbojka{kog meča. Prilagodljivost: Mogu se personalizovati programske funkcije prilagoćavajući ih sopstvenim kapacitetima: od odgovaranja tastature do procenjujuće tabele ve�������������������� {������������������� tina, od prikupljanja kriterijuma do {tampanja statističkih izve{taja. Kontolisani skauting: Analiza zone terena u kojima se ve{tine iznose – za svaku analizu moguće je vizualizovati četiri različite vrednosti koje pomažu treneru i za različite ve{tine da bi brzo identifikovao delove terena gde se najbolji i najgori potezi odigravaju. Analiza pravaca: Pokazuje pravac servisa i napada. Moguće je zahtevati potpunu, ili detaljnu, analizu bilo tima, igrača, pod određenim uslovima. DV-2 različitim bojama ističe savr{ene poteze, najlo{ije, kao i one između. Radna podloga: Zamenjuje pravu odbojka{ku povr{inu sa koje je moguće proučiti sve statističke podatke skautovanih mečeva. Zbog toga postoji mogućnost peronalizovanja prospekata analize zasnovanih na ličnim potrebama ubacujući veoma kompleksne formule. Pravac napada: Beleži efikasnost i pravac različitih napada zasnovanih na području napada, kvalitetu prijema itd. Detalji poslednjeg pogotka: Pokazuje na videu učinke poslednjeg pogotka svakog igrača, ve{tinu po ve{tinu u cilju „trenda“ da se svaki igrač proveri u svim tehničkim aspektima. HTLM izve{taj meča: Stvara statistički pregled meča u HTLM formatu radi objavljivanja na sopstvenom sajtu ili radi prosleđivanja istog drugim korisnicima preko mreže. Personalizacija ekrana analize: Pamti i {tampa kompleksne rasporede sastavljene od različitih prozora, a različitim tipovima analiza. Radi beleženja različitih kompleksnih faza analiza dopu{ta korisniku/treneru izbor personalizovanja programa za sopstvene potrebe. Data volej na klupi: Postoji mogućnost konekcije sa drugim kompjuterom na klupi sa koga se može konsultovati i proučavati podaci tokom meča – najče{će koriste mnogi mu{ki i ženski nacionalni timovi. Novi način praćenja bodova: DV-2 semafor program prikazuje zvanične poentere koristeći standardni video projektor, Personalization of the screen for analysis: It memorizes and prints out complex schedules comprised of different windows and containing different types of analysis. With the aim of identifying different complex phases, the analysis allows the user/coach to personalize the programme to suit their own needs. Data Volley on the bench: There is a possibility of connecting with another computer on the bench, from which one can consult and study the data during the match – this is mostly used by male and female national teams. 32 Zbornik radova 2010, 22-33 A new way of tracking scores: DV-2 score-board programme shows official pointers using a standard video projector, immediately transferring data from DV-2, as well as the logo, commercials, replay videos, etc. odmah prikazujući podatke od DV-2, kao i logo, reklame i ponovna prikazivanja, itd... Conclusion Cilj ovoga rada je bio da se objasni (prikažu mogućnosti i olak{ice) kako primena ve{tačke inteligencije (računarska disciplina čiji je zadatak da stvori računare koji mogu da rezonuju na način sličan ljudskom rezonovanju) pomaže u sportu. Implikacije neuronskih mreža na tehnologiju sportskog treninga postoje. Zahvaljujući prihvaćenim principima funcionisanja, neuronske mreže mogu značajno da unaprede efikasnost izvođenja pokreta sa jedne strane, a sa druge, efikasnije procesiranje brojnih inputa putem čulnih receptora u organizam. Prilikom izvođenja treninga, može da se na ovim principima razvije ekspertski sistem koji će se prilagoditi sportisti. To će sa jedne strane da minimizuje broj živih kontrolnih operatera, a sa druge da optimizuje trening sportiste, sprečavajući nastanak povreda uz maksimalni mogući parametarski progres. Elektronske igre i softverski agenti su sve vi{e prisutni i neophodni u sportu. Praktični aspekt ovog teorijskog istraživanja se ogleda u sistematizovanju i pro{irivanju znanja iz oblasti nauke/teorije sportskog treninga koja ima fundamentalni značaj za transer u praksu. Na taj način se podstiču stvaralačke ideje koje predstavljaju osnovu razvoja naučne misli iz oblasti sportskog treninga. The aim of this paper was to explain how an application of artificial intelligence (computer science discipline whose mission is to create computers which can imitate human reasoning processes) can be of assistance in sports. The implications of neural networks on technology of sports training is evident. Thanks to accepted principles of functioning, neural networks can on the one hand greatly improve the efficiency of body movements, and help a more effective processing of numerous input by means of sense receptors in the organism. During training, one can build an expert system following these principles, which is to be adjusted to the sportspeople. That would minimize the number of human control operators, and optimize the sports training itself, preventing getting injured with an optimal parameter progress. Electronic games and software agents are getting more and more present and necessary in sports. A practical aspect of this theoretical investigation is reflected in systematization and expansion of knowledge concerning science/theory of sports training, which has fundamental significance for transfer into practice. Thus, creative ideas are fostered, and they represent the basis for the development of scientific thought in the field of sports training. Reference Amit, D. (1989). Modeling Brain Functions: The World of Attractor Neural Nets. Cambridge: Cambridge University Press. Andrew, R., & Adams, E. (2006). Fundamentals of Game Design. London: Prentice Hall. Cvetković, D., Ostojić, M., & Ćosić, I. (2008). Sleep Onset Estimator: Evaluation of Parameters. Vankuver: EMBS. Hyacinth, S. N. (1996). Software Agents: An Overview. Knowledge Engineering Review, 11(3), 1–40. Received: October, 15th 2010 Correspodence to: \orđe Stefanović, PhD Faculty of Sports and Pnysical Education Blagoja Parovića 156 11000 Belgrade Serbia Phone: +381 11 35 31 000 E-mail: djordje.stefanovicªdif.bg.ac.rs Zaključak Kohonen, T. (1984). Self-Organization and Associative Memory. Berlin: Springer. Penrose, R. (1994). Shadows of the Mind. A Search for the Missing Science of Consciousness. Oxford: Oxford Univer. Press. Raković, D. (2008). Osnovi biofizike. Beograd: IASC & IEFPG. Stefanović, \. (2006). Teorija i praksa sportskog treninga. Beograd: Fakultet sporta i fizičkog vaspitanja. Stefanović, \., Jakovljević, S., & Janković, N. (2010). Tehnologija pripreme sportista. Beograd: Fakultet sporta i fizičkog vaspitanja. Primljeno: 15. oktobra 2010. godine Korespodencija: dr \orđe Stefanović Fakultet sporta i fizičkog vaspitanja Blagoja Parovića 156 11000 Beograd Srbija Telefon: +381 11 35 31 000 E-mail: djordje.stefanovicªdif.bg.ac.rs 33 INTRODUCTORY LECTURE UVODNO PREDAVANJE Stefanović, \.: SPORT I VE[TAČKA INTELIGENCIJA