• Study Resource
  • Explore
    • Arts & Humanities
    • Business
    • Engineering & Technology
    • Foreign Language
    • History
    • Math
    • Science
    • Social Science

    Top subcategories

    • Advanced Math
    • Algebra
    • Basic Math
    • Calculus
    • Geometry
    • Linear Algebra
    • Pre-Algebra
    • Pre-Calculus
    • Statistics And Probability
    • Trigonometry
    • other →

    Top subcategories

    • Astronomy
    • Astrophysics
    • Biology
    • Chemistry
    • Earth Science
    • Environmental Science
    • Health Science
    • Physics
    • other →

    Top subcategories

    • Anthropology
    • Law
    • Political Science
    • Psychology
    • Sociology
    • other →

    Top subcategories

    • Accounting
    • Economics
    • Finance
    • Management
    • other →

    Top subcategories

    • Aerospace Engineering
    • Bioengineering
    • Chemical Engineering
    • Civil Engineering
    • Computer Science
    • Electrical Engineering
    • Industrial Engineering
    • Mechanical Engineering
    • Web Design
    • other →

    Top subcategories

    • Architecture
    • Communications
    • English
    • Gender Studies
    • Music
    • Performing Arts
    • Philosophy
    • Religious Studies
    • Writing
    • other →

    Top subcategories

    • Ancient History
    • European History
    • US History
    • World History
    • other →

    Top subcategories

    • Croatian
    • Czech
    • Finnish
    • Greek
    • Hindi
    • Japanese
    • Korean
    • Persian
    • Swedish
    • Turkish
    • other →
 
Profile Documents Logout
Upload
NEWS RELEASE
NEWS RELEASE

AI and NLP – a fundamental approach
AI and NLP – a fundamental approach

... The brain is an active organ. However, without a definition of the active capabilities of natural intelligence, an Artificial Neural Network (ANN) is a passive network, no matter how many neurons are connected, and no matter its network configuration. ANN is a useful technique. However, it is only a ...
THE USE OF ARTIFICIAL INTELLIGENCE IN DIGITAL FORENSICS
THE USE OF ARTIFICIAL INTELLIGENCE IN DIGITAL FORENSICS

... match the current situation with one found in the case base. If a perfect match is found, then the action carried out in the initial case is applied to the existing situation. If no perfect match is found, but a match is found that is deemed to be close enough, then the system may attempt to adapt t ...
CHAPTER 11 INTELLIGENT SYSTEMS IN BUSINESS Oleh
CHAPTER 11 INTELLIGENT SYSTEMS IN BUSINESS Oleh

... Case (continued…) What have we learned from this case??  how an intelligent system solved a difficult business problem by improving the communication and collaboration between the company and its customers  the intelligent system solution was integrated with other information technologies (CD-ROM ...
Review of The Cognitive Structure of Emotions
Review of The Cognitive Structure of Emotions

Specific expert systems
Specific expert systems

... Edward Feigenbaum of Stanford University has defined expert system as “an intelligent computer program that uses knowledge and inference procedures to solve problems that are difficult enough to require significant human expertise for their solutions.” It is a branch of artificial intelligence intro ...
Intro
Intro

... SUBJECT NAME: BASIC COMPUTER SKILLS ...
Cyberethics - JSNE Group
Cyberethics - JSNE Group

... blend unobtrusively into our surroundings. Cybertechnology is also becoming less distinguishable from other technologies as boundaries that have previously separated them begin to blur because of convergence. ...
An Ontology-Based Symbol Grounding System for Human
An Ontology-Based Symbol Grounding System for Human

... The systems mentioned here, even if implicitly dealing with anchoring, lack a generic solution to the symbol grounding problem. They hard-code ad hoc solutions or use very small knowledge sets. Similarly, they often do not reason about multiple instances of the same type of object, either in the per ...
Lecture 1 , Jan - 14 - 2015
Lecture 1 , Jan - 14 - 2015

... Science is a systematic enterprise that builds and organizes ...
Operational Rationality through Compilation of Anytime Algorithms
Operational Rationality through Compilation of Anytime Algorithms

... react to a situation after performing the correct amount of thinking? My Ph.D. dissertation (Zilberstein 1993)2 presents a theoretical framework and a programming paradigm that provide an answer to this question. The solution is based on the replacement of standard modules of a program with more fle ...
A Model for Design of Societies of Cooperative Agents
A Model for Design of Societies of Cooperative Agents

... where agents are able to accomplish unsupervised actions The systems of CSDP, also known as systems for distributed reasoning, can be defined as systems composed by a set of separate modules and by a set of communication paths among them. These modules are frequently called agents, because it is sup ...
Multi-Agent Systems
Multi-Agent Systems

... Two main streams of definitions  Define an agent in isolation  Define an agent in the context of a society of agents  social dimension  MAS Two types of definitions  Does not necessary incorporate intelligence  Must incorporate a kind of IA behaviour  intelligent agents ...
MS PowerPoint format - Kansas State University
MS PowerPoint format - Kansas State University

... – Explicit: games of chance (e.g., backgammon, Monopoly) – Implicit: see project suggestions! ...
PDF - Carnegie Mellon School of Computer Science
PDF - Carnegie Mellon School of Computer Science

... the function Soβ which maps the elements in the set to truth and all other objects of type β to falsehood, and refer to Soβ as a set. Thus: Soβ xβ means that Soβ xβ is true. Soβ xβ means that xβ ∈ Soβ . Soβ = {xβ | Soβ xβ }. Similarly, Roβα is a relation between objects of type α and objects of type ...
No Slide Title
No Slide Title

... Imagination = visualization, modeling, & simulation Thought = analysis of what is imagined Reason = logic applied to thinking Emotion = value judgment, evaluation of good and bad Feeling = experience of sensory input Perception = transformation of sensation into knowledge Knowledge = organized infor ...
GO: Review of Work that has been done in this Area
GO: Review of Work that has been done in this Area

... This led to problems with the program’s underestimation of losing – or being ‘gammoned.’ BACKGAMMON: Current State of the Art TD-Gammon Vs. 3.0, written by Gerry Tesauro of IBM, replaced an earlier version of the game called Neurogammon. The program plays at a higher level than Neurogammon and has r ...
CDMTCS Research Report Series META
CDMTCS Research Report Series META

... In this article I’m going to concentrate on what we can prove about the foundations of mathematics using mathematical methods, in other words, on metamathematics. The current point of departure for metamathematics is that you’re doing mathematics using an artificial language and you pick a fixed set ...
Sborník vědeckých prací Vysoké školy báňské
Sborník vědeckých prací Vysoké školy báňské

... designed symbol system can provide a full causal account of intelligence, regardless of its medium of implementation; and • the empirical view of computer programs as experiments. As an empirical science, AI takes a constructive approach: we attempt to understand intelligence by building a working m ...
Document
Document

...  A problem is hard, if we are sure that there is not any polynomial-time algorithm to solve the problem (to get the optimal solution)..? ...
The Forthcoming Artificial Intelligence (AI) Revolution
The Forthcoming Artificial Intelligence (AI) Revolution

... invention” that may end human supremacy (Barat, 2013). There is little doubt that AI holds enormous potential as computers and robots will probably achieve, or come close to, human intelligence over the next twenty years becoming a serious competitor to all the jobs currently performed by humans and ...
Introduction to Hybrid Systems – Part 1
Introduction to Hybrid Systems – Part 1

... Knowledge in a rule-based expert system is represented by IF-THEN production rules. Knowledge in neural networks is stored as synaptic weights between neurons. ...
PDF document - Romanian
PDF document - Romanian

... with and use the appropriate information tools for business development, to enhance/validate their information gained through practice. The business component can generate a different kind of candidate who has to acquire a number of skills specific to the entrepreneur of an IT&C business. The MA com ...
Data and Knowledge Engineering for Intelligent Information Systems
Data and Knowledge Engineering for Intelligent Information Systems

... The conference on Applications of Declarative Programming and Knowledge Management (INAP–21) is collocated with two workshops on logic programming (WLP/WFLP). Previous INAP conferences have been held in Japan, Germany, Portugal, and Austria. ...
Artificial Intelligence I: introduction
Artificial Intelligence I: introduction

... In neural networks In uncertain reasoning and expert systems: Bayesian network ...
< 1 ... 108 109 110 111 112 113 114 115 116 ... 241 >

History of artificial intelligence

The history of artificial intelligence (AI) began in antiquity, with myths, stories and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen; as Pamela McCorduck writes, AI began with ""an ancient wish to forge the gods.""The seeds of modern AI were planted by classical philosophers who attempted to describe the process of human thinking as the mechanical manipulation of symbols. This work culminated in the invention of the programmable digital computer in the 1940s, a machine based on the abstract essence of mathematical reasoning. This device and the ideas behind it inspired a handful of scientists to begin seriously discussing the possibility of building an electronic brain.The field of AI research was founded at a conference on the campus of Dartmouth College in the summer of 1956. Those who attended would become the leaders of AI research for decades. Many of them predicted that a machine as intelligent as a human being would exist in no more than a generation and they were given millions of dollars to make this vision come true. Eventually it became obvious that they had grossly underestimated the difficulty of the project. In 1973, in response to the criticism of James Lighthill and ongoing pressure from congress, the U.S. and British Governments stopped funding undirected research into artificial intelligence. Seven years later, a visionary initiative by the Japanese Government inspired governments and industry to provide AI with billions of dollars, but by the late 80s the investors became disillusioned and withdrew funding again. This cycle of boom and bust, of ""AI winters"" and summers, continues to haunt the field. Undaunted, there are those who make extraordinary predictions even now.Progress in AI has continued, despite the rise and fall of its reputation in the eyes of government bureaucrats and venture capitalists. Problems that had begun to seem impossible in 1970 have been solved and the solutions are now used in successful commercial products. However, no machine has been built with a human level of intelligence, contrary to the optimistic predictions of the first generation of AI researchers. ""We can only see a short distance ahead,"" admitted Alan Turing, in a famous 1950 paper that catalyzed the modern search for machines that think. ""But,"" he added, ""we can see much that must be done.""
  • studyres.com © 2025
  • DMCA
  • Privacy
  • Terms
  • Report