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» Reinforcement Learning: An Introduction
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IAT
2010
IEEE
13 years 8 months ago
Multiagent Meta-level Control for a Network of Weather Radars
It is crucial for embedded systems to adapt to the dynamics of open environments. This adaptation process becomes especially challenging in the context of multiagent systems. In t...
Shanjun Cheng, Anita Raja, Victor R. Lesser
LR
2011
170views more  LR 2011»
13 years 5 months ago
Routing automated guided vehicles in container terminals through the Q-learning technique
This paper suggests a routing method for automated guided vehicles in port terminals that uses the Q-learning technique. One of the most important issues for the efficient operati...
Su Min Jeon, Kap Hwan Kim, Herbert Kopfer
CSL
2010
Springer
13 years 10 months ago
Bayesian update of dialogue state: A POMDP framework for spoken dialogue systems
This paper describes a statistically motivated framework for performing real-time dialogue state updates and policy learning in a spoken dialogue system. The framework is based on...
Blaise Thomson, Steve Young
ATAL
2009
Springer
14 years 4 months ago
Bounded rationality via recursion
Current trends in model construction in the field of agentbased computational economics base behavior of agents on either game theoretic procedures (e.g. belief learning, fictit...
Maciej Latek, Robert L. Axtell, Bogumil Kaminski
GECCO
2007
Springer
214views Optimization» more  GECCO 2007»
14 years 4 months ago
Portfolio allocation using XCS experts in technical analysis, market conditions and options market
Schulenburg [15] first proposed the idea to model different trader types by supplying different input information sets to a group of homogenous LCS agent. Gershoff [12] investigat...
Sor Ying (Byron) Wong, Sonia Schulenburg