34 search results - page 4 / 7 » Adapting Game-Playing Agents to Game Requirements |
AIIDE
2006
13 years 9 months ago
2006
Neuroevolution is a promising learning method in tasks with extremely large state and action spaces and hidden states. Recent advances allow neuroevolution to take place in real t...
ATAL
2005
Springer
14 years 1 months ago
2005
Springer
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
AIPS
2010
13 years 10 months ago
2010
Computing a good policy in stochastic uncertain environments with unknown dynamics and reward model parameters is a challenging task. In a number of domains, ranging from space ro...
AAAI
2008
13 years 10 months ago
2008
This paper examines, by argument, the dynamics of sequences of behavioural choices made, when non-cooperative restricted-memory agents learn in partially observable stochastic gam...
IJCAI
2007
13 years 9 months ago
2007
Multiagent distributed resource allocation requires that agents act on limited, localized information with minimum communication overhead in order to optimize the distribution of ...