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AAAI
1993
13 years 9 months ago
Complexity Analysis of Real-Time Reinforcement Learning
This paper analyzes the complexity of on-line reinforcement learning algorithms, namely asynchronous realtime versions of Q-learning and value-iteration, applied to the problem of...
Sven Koenig, Reid G. Simmons
ICML
2003
IEEE
14 years 8 months ago
Action Elimination and Stopping Conditions for Reinforcement Learning
We consider incorporating action elimination procedures in reinforcement learning algorithms. We suggest a framework that is based on learning an upper and a lower estimates of th...
Eyal Even-Dar, Shie Mannor, Yishay Mansour
AIIDE
2006
13 years 9 months ago
Designing a Reinforcement Learning-based Adaptive AI for Large-Scale Strategy Games
This paper investigates the challenges posed by the application of reinforcement learning to large-scale strategy games. In this context, we present steps and techniques which syn...
Charles A. G. Madeira, Vincent Corruble, Geber Ram...
FLAIRS
2008
13 years 10 months ago
Reinforcement of Local Pattern Cases for Playing Tetris
In the paper, we investigate the use of reinforcement learning in CBR for estimating and managing a legacy case base for playing the game of Tetris. Each case corresponds to a loc...
Houcine Romdhane, Luc Lamontagne
NIPS
2000
13 years 9 months ago
Programmable Reinforcement Learning Agents
We present an expressive agent design language for reinforcement learning that allows the user to constrain the policies considered by the learning process.The language includes s...
David Andre, Stuart J. Russell