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GECCO
2009
Springer
15 years 5 months ago
Novelty of behaviour as a basis for the neuro-evolution of operant reward learning
An agent that deviates from a usual or previous course of action can be said to display novel or varying behaviour. Novelty of behaviour can be seen as the result of real or appar...
Andrea Soltoggio, Ben Jones
JMLR
2012
13 years 3 months ago
Hierarchical Relative Entropy Policy Search
Many real-world problems are inherently hierarchically structured. The use of this structure in an agent’s policy may well be the key to improved scalability and higher performa...
Christian Daniel, Gerhard Neumann, Jan Peters
128
Voted
ATAL
2004
Springer
15 years 6 months ago
Learning User Preferences for Wireless Services Provisioning
The problem of interest is how to dynamically allocate wireless access services in a competitive market which implements a take-it-or-leave-it allocation mechanism. In this paper ...
George Lee, Steven Bauer, Peyman Faratin, John Wro...
96
Voted
ATAL
2008
Springer
15 years 2 months ago
Non-linear dynamics in multiagent reinforcement learning algorithms
Several multiagent reinforcement learning (MARL) algorithms have been proposed to optimize agents' decisions. Only a subset of these MARL algorithms both do not require agent...
Sherief Abdallah, Victor R. Lesser
JMLR
2006
153views more  JMLR 2006»
15 years 22 days ago
Collaborative Multiagent Reinforcement Learning by Payoff Propagation
In this article we describe a set of scalable techniques for learning the behavior of a group of agents in a collaborative multiagent setting. As a basis we use the framework of c...
Jelle R. Kok, Nikos A. Vlassis