25 search results - page 2 / 5 » Learning by demonstration in repeated stochastic games |
AI
2007
Springer
13 years 11 months ago
2007
Springer
Agent competition and coordination are two classical and most important tasks in multiagent systems. In recent years, there was a number of learning algorithms proposed to resolve ...
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
This paper introduces a novel multiagent learning algorithm, Convergence with Model Learning and Safety (or CMLeS in short), which achieves convergence, targeted optimality agains...
IJCAI
2001
13 years 6 months ago
2001
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
ICML
2008
IEEE
14 years 6 months ago
2008
IEEE
Typically agent evaluation is done through Monte Carlo estimation. However, stochastic agent decisions and stochastic outcomes can make this approach inefficient, requiring many s...
AI
2002
Springer
13 years 5 months ago
2002
Springer
Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on ...