DocumentCode :
2453345
Title :
Learning Collaborative Behavior by Observation
Author :
Johnson, Cynthia L. ; Gonzalez, Avelino J.
Author_Institution :
Dept of Electr. Eng. & Comput. Sci., Univ. of Central Florida, Orlando, FL, USA
fYear :
2010
fDate :
12-14 Dec. 2010
Firstpage :
99
Lastpage :
104
Abstract :
This paper presents a multi-agent framework capable of learning teamwork by observation. The system combines proven single entity learning by observation techniques with a multi-agent system shown to exhibit effective teamwork. An effective simulated production team is observed. An off-line training algorithm uses the observed data to develop behavior maps for a Collaborative Context-based Reasoning framework. The Collaborative Context-based Reasoning framework provides generic base classes capable of recreating the behavior of the original agents using the behavior maps developed by the training algorithm. The resulting prototype effectively replaces the original team of agents and is capable of reproducing its behavior and generalizing the behavior to encompass similar situations.
Keywords :
inference mechanisms; learning (artificial intelligence); multi-agent systems; behavior maps; collaborative context-based reasoning framework; learning collaborative behavior; learning teamwork; multiagent framework; multiagent system; observation; offline training algorithm; single entity learning; Context; Prototypes; Robots; Teamwork; Training; Unified modeling language; Water resources; learning by observation; multi-agent learning; teamwork;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Applications (ICMLA), 2010 Ninth International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4244-9211-4
Type :
conf
DOI :
10.1109/ICMLA.2010.22
Filename :
5708819
Link To Document :
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