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Titlebook: Autonomous Agents; George A. Bekey Book 1998 Kluwer Academic Publishers 1998 Emission.Motor.artificial intelligence.autonom.autonomous age

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楼主: Ensign
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Recursive Information Granulationand the host incrementally generates the most plausible map of the environment. To perform the map generation, a fusion, completion and alignment process of the partial maps, based on fuzzy techniques, has been developed.
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Basic Visual and Motor Agents for Increasingly Complex Behavior Generation on a Mobile Robot,e raised under a space-variant representation pursuing an anthropomorphic approach. We illustrate how a complex behavior results from the combination of lower level agents always connected to the basic motor agents. The proposed methodology is validated on a caterpillar mobile robot in navigation tasks directed by an object description.
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Map Generation by Cooperative Low-Cost Robots in Structured Unknown Environments,and the host incrementally generates the most plausible map of the environment. To perform the map generation, a fusion, completion and alignment process of the partial maps, based on fuzzy techniques, has been developed.
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Random-Sets: Theory and Applications,dals, unary predicates, and functions. We describe an example using Kludge, a vision-based mobile robot programmed to perform simple natural language instructions involving fetching and following tasks.
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Learning View Graphs for Robot Navigation, model of the environment. To navigate between views connected in the graph, we employ a homing strategy inspired by findings of insect ethology. In robot experiments, we demonstrate that complex visual exploration and navigation tasks can thus be performed without using metric information.
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Granular Computing Based Machine Learningexecution of a mission to be allocated among the human and artificial agents. Our implementation and demonstrations (in real robots and simulations) of our multi-agent system shows significant promise for the integration of unmanned vehicles in military applications.
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