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» Programmable Reinforcement Learning Agents
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AAAI
2010
13 years 10 months ago
Learning Simulation Control in General Game-Playing Agents
The aim of General Game Playing (GGP) is to create intelligent agents that can automatically learn how to play many different games at an expert level without any human interventi...
Hilmar Finnsson, Yngvi Björnsson
IJCNN
2006
IEEE
14 years 2 months ago
Training Coordination Proxy Agents
— Delegating the coordination role to proxy agents can improve the overall outcome of the task at the expense of cognitive overload due to switching subtasks. Stability and commi...
Myriam Abramson, William Chao, Ranjeev Mittu
ATAL
2009
Springer
13 years 6 months ago
Decentralized Learning in Wireless Sensor Networks
In this paper we use a reinforcement learning algorithm with the aim to increase the autonomous lifetime of a Wireless Sensor Network (WSN) and decrease latency in a decentralized...
Mihail Mihaylov, Karl Tuyls, Ann Nowé

Publication
233views
12 years 7 months ago
Sparse reward processes
We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained duri...
Christos Dimitrakakis
AAMAS
2005
Springer
13 years 8 months ago
Cooperative Multi-Agent Learning: The State of the Art
Cooperative multi-agent systems are ones in which several agents attempt, through their interaction, to jointly solve tasks or to maximize utility. Due to the interactions among t...
Liviu Panait, Sean Luke