intelligent_agents - Intelligent Agents With Java 1 Focus...

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1 Intelligent Agents With Java
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2 Focus of talk A basic look at agent-based reasoning, modeling, and learning How agents can enhance the capability and productivity of commercial application software The effect of agents on the Web, with a Java twist
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3 Artificial Intelligence: Introduction The science of AI is approximately forty years dating back to a conference at Dartmouth in 1958 The public perception of AI has not always matched the reality The excitement of both scientists and the popular press tended to overstate the real-world progress of artificial intelligent systems Early success promised rapid progress towards practical machines intelligence. Areas of early successes Game playing, mathematical theorem proving, common- sense reasoning, college mathematics
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4 Introduction, contd. AI research labs began specializing in narrow fields Speech recognition Natural language understanding Image optical character recognition The early successes were followed by a slow realization that things that humans do with very little effort was near impossible for the computer What was hard for people and easy for the computer was more than offset by the things that were easy for people to do but almost impossible for computers to do
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5 Introduction, contd. The promise of the early years has never been fully realized The term artificial intelligence have become associated with failure and over-hyped technology Nevertheless, researchers in AI have made significant contributions to computer science WIMP (Windows, icon, mouse, pointer) user interface Considered highly controversial and impractical when first introduce by the IA community Object-oriented programming techniques Refinement of the AI Frames concept
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6 Basic Concepts AI has always focused on problems which lie just beyond the reach of state-of-the-art computers Effectively pushing the current bleeding-edge technologies As computer science and computer systems evolved, the focus and areas which falls into AI research have also changed We can identify three major phases of development in AI research
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7 First Phase Much of this work dealt with formal problems that were structured and had well-defined problem boundaries Math related skills: proving theorems, geometry, calculus, games (checkers, chess) Emphasis was on creating general “ thinking machines ” capable of solving broad classes of problems These systems tended to include sophisticated capabilities relating to reasoning and search techniques
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8 Second Phase Marked by the recognition that the most successful AI projects were aimed at very narrow problem domains These systems usually encoded much specific knowledge about the problem to be solved This approach of adding specific domain knowledge to a more general reasoning system led to the commercial success in AI – Expert Systems . Rule-based expert systems were developed to do many
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This note was uploaded on 07/14/2011 for the course COP 4910 taught by Professor Williams during the Summer '10 term at University of Central Florida.

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intelligent_agents - Intelligent Agents With Java 1 Focus...

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