Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/7343
Title: Interaction and Intelligent Behavior
Keywords: group behavior
learning
multi-agent systems
situated agents
behavior-based control
collective behavior
Issue Date: 9-Oct-2013
Description: We introduce basic behaviors as primitives for control and learning in situated, embodied agents interacting in complex domains. We propose methods for selecting, formally specifying, algorithmically implementing, empirically evaluating, and combining behaviors from a basic set. We also introduce a general methodology for automatically constructing higher--level behaviors by learning to select from this set. Based on a formulation of reinforcement learning using conditions, behaviors, and shaped reinforcement, out approach makes behavior selection learnable in noisy, uncertain environments with stochastic dynamics. All described ideas are validated with groups of up to 20 mobile robots performing safe--wandering, following, aggregation, dispersion, homing, flocking, foraging, and learning to forage.
URI: http://koha.mediu.edu.my:8181/xmlui/handle/1721
Other Identifiers: AITR-1495
http://hdl.handle.net/1721.1/7343
Appears in Collections:MIT Items

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