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103
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IWANN
1999
Springer
15 years 5 months ago
Using Temporal Neighborhoods to Adapt Function Approximators in Reinforcement Learning
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
R. Matthew Kretchmar, Charles W. Anderson
127
Voted
ATAL
2007
Springer
15 years 4 months ago
Resolving conflict and inconsistency in norm-regulated virtual organizations
Norm-governed virtual organizations define, govern and facilitate coordinated resource sharing and problem solving in societies of agents. With an explicit account of norms, openn...
Wamberto Weber Vasconcelos, Martin J. Kollingbaum,...
85
Voted
ICCBR
2010
Springer
15 years 4 months ago
Imitating Inscrutable Enemies: Learning from Stochastic Policy Observation, Retrieval and Reuse
In this paper we study the topic of CBR systems learning from observations in which those observations can be represented as stochastic policies. We describe a general framework wh...
Kellen Gillespie, Justin Karneeb, Stephen Lee-Urba...
ATAL
2006
Springer
15 years 4 months ago
Efficient agent-based cluster ensembles
Numerous domains ranging from distributed data acquisition to knowledge reuse need to solve the cluster ensemble problem of combining multiple clusterings into a single unified cl...
Adrian K. Agogino, Kagan Tumer
109
Voted
CLIMA
2007
15 years 2 months ago
Plan-Coordination Mechanisms and the Price of Autonomy
Abstract. Task-based planning problems for multi-agent systems require multiple agents to find a joint plan for a constrained set of tasks. Typically, each agent receives a subset...
J. Renze Steenhuisen, Cees Witteveen, Yingqian Zha...