By Roberto A. Flores, Robert C. Kremer (auth.), Ahmed Y. Tawfik, Scott D. Goodwin (eds.)
This ebook constitutes the refereed complaints of the seventeenth convention of the Canadian Society for Computational reports of Intelligence, Canadian AI 2004, held in London, Ontario, Canada in may perhaps 2004.
The 29 revised complete papers and 22 revised brief papers have been conscientiously reviewed and chosen from one hundred and five submissions. those papers are provided including the prolonged abstracts of 14 contributions to the graduate scholars' song. the entire papers are equipped in topical sections on brokers, common language processing, studying, constraint pride and seek, wisdom illustration and reasoning, uncertainty, and neural networks.
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For cross-exclusion to work, the inhibitory values must be set high enough to ensure that there is no flip-flopping of states after one need is satisfied. We determined these values through trial and error, although it would be possible to automate this process using, for instance, an evolutionary algorithm. Among humans, different people have different thresholds for hunger, thirst, and so on, thus there is no one best set of threshold values. Indeed, since the ultimate goal is to create agents that do interesting things in the context of games or movies, we want to keep the ability to experiment with unusual parameter values.
These two components, central to the implementation of blended teleautonomy, are described in the remainder of this section. Peripheral components such as the user interface are described fully in . 1 Mediator The mediation component is responsible for smoothly integrating the operator’s commands with those of an agent’s autonomous control system. While previous approaches have focused on blending operator instructions directly with instructions from an autonomous controller, our approach is more flexible, allowing the agent to intelligently evaluate instructions before blending to ensure that instructions are safe and appropriate to execute.
To blend autonomy and teleoperation appropriately, the agent is capable of reasoning about commands that have been sent to it from the human operator. Some commands may be followed to the letter, while others integrated with the agent’s own desires or completely refused. The latter allows the veto of actions that would put the robot in danger inadvertently, such as being told to move forward when the operator is not necessarily aware the robot is on the edge of a drop. e. the value of information obtained is worth the potential loss of the robot), and so it is also possible for the mediator to allow the operator’s commands to be unquestioned.
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.)