Advanced Search
DSpace@MIT

Interaction and Intelligent Behavior

Research and Teaching Output of the MIT Community

Show simple item record

dc.contributor.author Mataric, Maja J. en_US
dc.date.accessioned 2004-11-19T17:19:50Z
dc.date.available 2004-11-19T17:19:50Z
dc.date.issued 1994-08-01 en_US
dc.identifier.other AITR-1495 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/7343
dc.description.abstract 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. en_US
dc.format.extent 177 p. en_US
dc.format.extent 15039745 bytes
dc.format.extent 1008036 bytes
dc.format.mimetype application/postscript
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.relation.ispartofseries AITR-1495 en_US
dc.subject group behavior en_US
dc.subject learning en_US
dc.subject multi-agent systems en_US
dc.subject situated agents en_US
dc.subject behavior-based control en_US
dc.subject collective behavior en_US
dc.title Interaction and Intelligent Behavior en_US


Files in this item

Name Size Format Description
AITR-1495.ps 14.34Mb Postscript
AITR-1495.pdf 984.4Kb PDF

This item appears in the following Collection(s)

Show simple item record

MIT-Mirage