Download PDF by Roberto A. Flores, Robert C. Kremer (auth.), Ahmed Y.: Advances in Artificial Intelligence: 17th Conference of the

By Roberto A. Flores, Robert C. Kremer (auth.), Ahmed Y. Tawfik, Scott D. Goodwin (eds.)

ISBN-10: 3540220046

ISBN-13: 9783540220046

ISBN-10: 3540248404

ISBN-13: 9783540248408

This e-book constitutes the refereed lawsuits of the seventeenth convention of the Canadian Society for Computational reports of Intelligence, Canadian AI 2004, held in London, Ontario, Canada in may well 2004.

The 29 revised complete papers and 22 revised brief papers have been conscientiously reviewed and chosen from one zero five submissions. those papers are offered including the prolonged abstracts of 14 contributions to the graduate scholars' music. the whole papers are equipped in topical sections on brokers, normal language processing, studying, constraint pride and seek, wisdom illustration and reasoning, uncertainty, and neural networks.

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Read Online or Download Advances in Artificial Intelligence: 17th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2004, London, Ontario, Canada, May 17-19, 2004. Proceedings PDF

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Additional resources for Advances in Artificial Intelligence: 17th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2004, London, Ontario, Canada, May 17-19, 2004. Proceedings

Sample text

Immediately after the user selects the GOAL, A* is run to find a best path, and when its done, the knight begins walking along the path. If an obstacle moves into its path after it is has finished searching, then it will need to re-plan its path. As mentioned, A* search can eat up significant amounts of time and memory, and so in real-time applications (like games) sometimes an answer must be given before the algorithm has finished. In such cases, the knight may need to make moves before it knows the best path to follow.

Are encoded in the form of motor schemas, which are activated by perceptual schemas (defining perceptual items of interest) and interact at run time to produce output to robot effectors. The first approach has the operator’s control (input from a joystick) as a behavior that influences the robots’ effectors just as any internal behavior does. The second approach for teleautonomy involves having the operator act as a supervisor. g. the low level gains of each motor schema). The operator could effect the emergent behavior of the society of agents as a whole by adjusting their behavioral parameters.

Teleautonomous agents performed significantly better than autonomous agents in terms of area coverage across all degrees of obstacle coverage. We attribute this performance to a human operator’s ability to recognize unexplored areas of the environment quickly and guide agents to unexplored areas more efficiently then the autonomous control system could. Some unexplored areas were unlikely to be found by the autonomous agents because of the unique obstacle configurations in those unexplored areas.

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Advances in Artificial Intelligence: 17th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2004, London, Ontario, Canada, May 17-19, 2004. Proceedings by Roberto A. Flores, Robert C. Kremer (auth.), Ahmed Y. Tawfik, Scott D. Goodwin (eds.)


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