By Ahmed Y. Tawfik, Scott D. Goodwin
This publication constitutes the refereed complaints of the seventeenth convention of the Canadian Society for Computational stories of Intelligence, Canadian AI 2004, held in London, Ontario, Canada in might 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 provided including the prolonged abstracts of 14 contributions to the graduate scholars' music. the whole papers are prepared in topical sections on brokers, typical language processing, studying, constraint pride and seek, wisdom illustration and reasoning, uncertainty, and neural networks.
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Extra resources for Advances in Artificial Intelligence: 17th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2004, London, Ontario,
If the agent surpasses the threshold, then it is identified as confused. The system is extendible since new intervention events can be coded as additional intervention event objects. 4 Evaluation In order to examine the performance of this approach, we placed agents in a controlled simulated USAR environment implemented using the Player/Stage simulation tool . Player/Stage was chosen because it is widely used and allows development of code that operates directly on Pioneer robots. Each robot was a Pioneer II equipped with a differential drive, a SICK laser range scanner and a video (CCD) camera with a wide angle lens.
Emotions for objects are liking and disliking. Agent emotions include pride, shame, reproach, and admiration. It assumes that emotions are valenced reactions; the intensity of an affective reactions determines whether or not it will be experienced as emotions. Processing an emotion consists of four steps: classifying input stimulus, quantifying the intensity of emotions, mapping intensities to emotional expressions, and, finally, realizing those emotional expressions. One of the reasons that this model is popular among artificial intelligence community is that the processing stages can be implemented in a straightforward way using rules .
Fig. 8. Average (n=5) ratio of operator interactions (teleoperated/blended teleautonomous in environments with 5, 10, 15, and 20% obstacle coverage. 5 Future Work There are a number of directions that future work in this area can profitably take. In terms of immediate further experimentation, we are currently examining the efficacy of this approach as the number of robots increases, both to examine how far the benefits obtained can be pushed, and to help identify future improvements that will allow the operator to better control larger teams of agents.
Advances in Artificial Intelligence: 17th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2004, London, Ontario, by Ahmed Y. Tawfik, Scott D. Goodwin