166 search results - page 14 / 34 » Online model learning in adversarial Markov decision process... |
ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
How should a reinforcement learning agent act if its sole purpose is to efficiently learn an optimal policy for later use? In other words, how should it explore, to be able to exp...
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ICML
1998
IEEE
15 years 10 months ago
1998
IEEE
Production scheduling, the problem of sequentially con guring a factory to meet forecasted demands, is a critical problem throughout the manufacturing industry. The requirement of...
CONNECTION
2008
14 years 9 months ago
2008
Spoken language is one of the most intuitive forms of interaction between humans and agents. Unfortunately, agents that interact with people using natural language often experienc...
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ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
CORR
2010
Springer
14 years 9 months ago
2010
Springer
Markov decision processes (MDPs) are widely used for modeling decision-making problems in robotics, automated control, and economics. Traditional MDPs assume that the decision mak...