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NIPS
2008
14 years 11 months ago
Regularized Policy Iteration
In this paper we consider approximate policy-iteration-based reinforcement learning algorithms. In order to implement a flexible function approximation scheme we propose the use o...
Amir Massoud Farahmand, Mohammad Ghavamzadeh, Csab...
GECCO
2005
Springer
154views Optimization» more  GECCO 2005»
15 years 3 months ago
Combining competent crossover and mutation operators: a probabilistic model building approach
This paper presents an approach to combine competent crossover and mutation operators via probabilistic model building. Both operators are based on the probabilistic model buildin...
Cláudio F. Lima, Kumara Sastry, David E. Go...
NECO
2007
150views more  NECO 2007»
14 years 9 months ago
Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
Dorit Baras, Ron Meir
ATAL
2008
Springer
15 years 3 days ago
Switching dynamics of multi-agent learning
This paper presents the dynamics of multi-agent reinforcement learning in multiple state problems. We extend previous work that formally modelled the relation between reinforcemen...
Peter Vrancx, Karl Tuyls, Ronald L. Westra
CSREAEEE
2008
199views Business» more  CSREAEEE 2008»
14 years 11 months ago
Progranimate - A Web Enabled Algorithmic Problem Solving Application
- This paper proposes the use of an interactive web based problem solving application that utilises flowchart based programming and code generation to address the issues faced by n...
Andrew Scott, Mike Watkins, Duncan McPhee