Interaction and Intelligent Behavior


Autoria(s): Mataric, Maja J.
Data(s)

19/11/2004

19/11/2004

01/08/1994

Resumo

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.

Formato

177 p.

15039745 bytes

1008036 bytes

application/postscript

application/pdf

Identificador

AITR-1495

http://hdl.handle.net/1721.1/7343

Idioma(s)

en_US

Relação

AITR-1495

Palavras-Chave #group behavior #learning #multi-agent systems #situated agents #behavior-based control #collective behavior