* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project
Copyright R. Weber INFO 629 Concepts in Artificial Intelligence Fall 2004 Professor: Dr. Rosina Weber Copyright R. Weber My introduction • Assistant Professor, Information Science & Technology, Drexel University • Navy Center for Applied Research in Artificial Intelligence, Naval Research Lab • Doctoral degree from Production Engineering Program (UFSC, SC/BRAZIL + USF, FL/USA) • Master’s degree in Artificial Intelligence & Operations Research • Bachelor’s Business Administration • Industry experience • Solving knowledge management problems with CI/AI methods, particularly CBR • Publications at http://www.pages.drexel.edu/~rw37/publications.html Copyright R. Weber INFO 629 topics 1. 2. 3. 4. 5. 6. 7. Expert Systems Intelligent Tutoring Systems Case-based reasoning Search Machine Learning, Data Mining Neural Networks, Genetic Algorithms Natural Language Processing Copyright R. Weber What is AI? Why do we need AI ? Copyright R. Weber Introduction to AI • • • • definition of AI AI concepts AI tasks AI applications Copyright R. Weber What is AI? Copyright R. Weber What’s your definition of AI? Copyright R. Weber What is AI (from R&N) Copyright R. Weber What is AI (from R&N) Copyright R. Weber What is AI (from R&N) Copyright R. Weber What is AI (from R&N) Copyright R. Weber What is AI (from R&N) Copyright R. Weber Artificial Intelligence Artificial Intelligence is the study of computational models to perform tasks normally associated with rational behavior manifested as reasoning, perception, and appropriate actions and reactions. Copyright R. Weber Artificial Intelligence Artificial Intelligence is the field of study dedicated to the study and design of computational models that perform tasks that are typically considered “human”. These tasks may entail use of knowledge, reasoning, or physical abilities. Copyright R. Weber Artificial Intelligence •Study and design of computational models (purposes, methods) – Study, solve problems e.g. assisting, replacing – Methods use techniques that are new or adapted from other fields •Perform tasks – What are AI tasks? •Typically considered “human” – Mundane, expert, physical (complex) Copyright R. Weber AI tasks Copyright R. Weber AI tasks (complex) • reading & understanding • diagnosis • configuration • categorization • classification • creativity • discovery • speech recognition & synthesis • obstacle avoidance • NL generation • NL understanding • • • • • • • • planning scheduling design prediction control monitoring analysis vision Copyright R. Weber Types of AI tasks • mundane: – face recognition – argumentation – shopping planning • expert: – – – – diet prescription medical diagnosis legal argumentation legal, military, business planning • Solution oriented: – Knowledge discovery – Text mining Copyright R. Weber AI tasks and AI problems • AI problem is natural language, whereas related AI tasks are composition, speech, reading and understanding • Examples of AI problems can be mechanical or medical diagnosis and the AI task in both is diagnosis • An AI problem is one that requires the performance of one or many AI tasks to be solved Copyright R. Weber AI applications Copyright R. Weber a complete demo http://www.sls.lcs.mit.edu/sls/whatwedo/applications/jupiter.html 1-888-573-8255 Copyright R. Weber applications of AI (i) • knowledge based systems – financial advise – medical diagnosis, credit analysis – case-based reasoning systems for forecasting, case retrieval, prescription of diet, exercise – knowledge management systems – creativity, planning, forecast, recommender, personalization, argumentation, mediation, tutoring systems (education), • military applications – HICAP – Immersive Training Environments with virtual reality Copyright R. Weber applications of AI (ii) • machine learning, neural networks – pattern recognition, e.g., penmanship, voice, brain activity patterns of motor areas http://www.txtwriter.com/Onscience/Articles/ratrobot.html – analyze trends in any domain, knowledge discovery in databases and text, e.g., data mining – classification and clustering and adaptation, collaborative filtering (movielens) Copyright R. Weber applications of AI (iii) • problem solving by search –genetic algorithms, games • robotics, vision –search for survivors after earthquakes • recognize survivors • obstacle avoidance http://www.nsf.gov/od/lpa/news/03/pr0391_video1.htm -recognizing criminals in random public locations –unmanned airplanes, search for land mines –intelligent user interfaces Copyright R. Weber applications of AI (iv) • natural language – natural language interfaces – machine translation http://babelfish.altavista.com/ – text understanding to analyze patterns & trends – summarization, information extraction • uncertainty – represent and reason with elements that are vague and uncertain – use of fuzzy sets and statistical methods Dialogue-based NL • http://www.alicebot.org/ • Winner of the Loebner Prize 2000 & 2001. JUDGE05[02:19:03] MY NAME IS JUDGE05 PROGRAM[02:19:03] It's good to meet you, PROGRAM[02:19:03] Judge05. JUDGE05[02:19:16] You too. What is your name? JUDGE05[02:19:16] PROGRAM[02:19:16] Bless you. PROGRAM[02:19:16] My name is ALICE. JUDGE05[02:19:37] Good morning Alice. Why have you entered the Loebner Prize? JUDGE05[02:19:37] PROGRAM[02:19:37] Hello and how are you this morning? PROGRAM[02:19:37] The Loebner Prize PROGRAM[02:19:37] is an annual Turing Test sponsored by New York philanthropist Hugh Loebner. Dr. Wallace and ALICE won it in 2000 Copyright R. Weber • more chatbots • http://www.alicebot.org/live.html • more transcripts at http://loebner.net/Prizef/2001_Contest/loebner-prize-2001.html Copyright R. Weber Necessary grounds for computer understanding • Ability to represent knowledge and reason with it. • Perceive equivalences and analogies between two different representations of the same entity/situation. • Learning and reorganizing new knowledge. – From Peter Jackson (1998) Introduction to Expert systems. Addison-Wesley third edition. Chapter 2, page 27.