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ECAI
2006
Springer
13 years 10 months ago
Strategic Foresighted Learning in Competitive Multi-Agent Games
We describe a generalized Q-learning type algorithm for reinforcement learning in competitive multi-agent games. We make the observation that in a competitive setting with adaptive...
Pieter Jan't Hoen, Sander M. Bohte, Han La Poutr&e...
AROBOTS
1999
104views more  AROBOTS 1999»
13 years 6 months ago
Reinforcement Learning Soccer Teams with Incomplete World Models
We use reinforcement learning (RL) to compute strategies for multiagent soccer teams. RL may pro t signi cantly from world models (WMs) estimating state transition probabilities an...
Marco Wiering, Rafal Salustowicz, Jürgen Schm...
ROBOCUP
2004
Springer
114views Robotics» more  ROBOCUP 2004»
14 years 11 days ago
Modular Learning System and Scheduling for Behavior Acquisition in Multi-agent Environment
The existing reinforcement learning approaches have been suffering from the policy alternation of others in multiagent dynamic environments such as RoboCup competitions since othe...
Yasutake Takahashi, Kazuhiro Edazawa, Minoru Asada
IPPS
2008
IEEE
14 years 1 months ago
CoSL: A coordinated statistical learning approach to measuring the capacity of multi-tier websites
Website capacity determination is crucial to measurement-based access control, because it determines when to turn away excessive client requests to guarantee consistent service qu...
Jia Rao, Cheng-Zhong Xu
ICML
2005
IEEE
14 years 7 months ago
Bayesian sparse sampling for on-line reward optimization
We present an efficient "sparse sampling" technique for approximating Bayes optimal decision making in reinforcement learning, addressing the well known exploration vers...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...