Spelling suggestions: "subject:"mutual inhibition"" "subject:"vutual inhibition""
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Structure Learning of a Behavior Network for Context Dependent AdaptabilityLi, Ou 07 December 2006 (has links)
One mechanism for an intelligent agent to adapt to substantial environmental changes is to change its decision making structure. Pervious work in this area has developed a context-dependent behavior selection architecture that uses structure change, i.e., changing the mutual inhibition structures of a behavior network, as the main mechanism to generate different behavior patterns according to different behavioral contexts. Given the important of network structure, this work investigates how the structure of a behavior network can be learned. We developed a structure learning method based on generic algorithm and applied it to a model crayfish that needs to survive in a simulated environment. The model crayfish is controlled by a mutual inhibition behavior network, whose structures are learned using the GA-based algorithm for different environment configurations. The results show that it is possible to learn robust and consistent network structures allowing intelligent agents to behave adaptively in a particular environment.
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Robot-In-The-Loop Simulation to Support Multi-Robot System Development: A Dynamic Team Formation ExampleAzarnasab, Ehsan 03 May 2007 (has links)
Modeling and simulation provides a powerful technology for engineers and managers to understand, design, and evaluate a system under development. Traditionally, simulation is only used in early stages of a system design. However, with the advances of hardware and software technology, it is now possible to extend simulation to late stages for supporting a full life cycle simulation-based development. Robot-in-the-loop simulation, where real robots work together with virtual ones, has been developed to support such a development process to bridge the gap between simulation and reality.
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