Get Advances in Artificial Intelligence: 17th Conference of the PDF

By Ahmed Y. Tawfik, Scott D. Goodwin

This publication constitutes the refereed court cases of the seventeenth convention of the Canadian Society for Computational reports of Intelligence, Canadian AI 2004, held in London, Ontario, Canada in may possibly 2004. The 29 revised complete papers and 22 revised brief papers have been conscientiously reviewed and chosen from a hundred and five submissions. those papers are offered including the prolonged abstracts of 14 contributions to the graduate scholars' tune. the entire papers are equipped in topical sections on brokers, average language processing, studying, constraint pride and seek, wisdom illustration and reasoning, uncertainty, and neural networks.

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In highly complex domains such as disaster rescue, today’s autonomous agents simply do not have the ability to perform successfully on their own: the environment is difficult to traverse and to sense accurately, time is a significant factor, and the unpredictable nature of the environment tends to preclude the ability to produce extensive plans for future activity. In this paper we describe an approach to multi-robot control for such environments that focuses on combining the limited abilities of a modern autonomous agent together with human control, in order to produce a teleautonomous system that supports blending the desires of a robot with the wishes of its human controller.

8). Even with the additional attention required by the more dense environments, the blending control system required less attention from the operator, which contributes to a lower cognitive load. 28 R. Wegner and J. Anderson Fig. 7. Comparison of number of victims identified in teleoperated, autonomous, and blending experiments in environments where 20% was covered in obstacles. All results are averages over 5 trials. Fig. 8. Average (n=5) ratio of operator interactions (teleoperated/blended teleautonomous in environments with 5, 10, 15, and 20% obstacle coverage.

In C. L. Johnson, editors, Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, pages 527–534, Bologna, Italy, July 2002. ca Abstract. In highly complex domains such as disaster rescue, today’s autonomous agents simply do not have the ability to perform successfully on their own: the environment is difficult to traverse and to sense accurately, time is a significant factor, and the unpredictable nature of the environment tends to preclude the ability to produce extensive plans for future activity.

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