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AGENTS
1999
Springer
13 years 10 months ago
General Principles of Learning-Based Multi-Agent Systems
We consider the problem of how to design large decentralized multiagent systems (MAS’s) in an automated fashion, with little or no hand-tuning. Our approach has each agent run a...
David Wolpert, Kevin R. Wheeler, Kagan Tumer
ATAL
2005
Springer
13 years 11 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
GAMEON
2003
13 years 7 months ago
Automatic Acquisition of Actions for Animated Agents
The generation of animated human figures especially in crowd scenes has many applications in such domains as the special effects industry, computer games or for the simulation of ...
Adam Szarowicz, Marek Mittmann, Paolo Remagnino, J...
GECCO
2009
Springer
109views Optimization» more  GECCO 2009»
13 years 10 months ago
A genetic algorithm for learning significant phrase patterns in radiology reports
Radiologists disagree with each other over the characteristics and features of what constitutes a normal mammogram and the terminology to use in the associated radiology report. R...
Robert M. Patton, Thomas E. Potok, Barbara G. Beck...
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
13 years 3 months ago
Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Tobias Jung, Peter Stone