13 search results - page 1 / 3 » On-line evolutionary computation for reinforcement learning ... |
GECCO
2006
Springer
14 years 1 months ago
2006
Springer
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
AAAI
2010
13 years 10 months ago
2010
This paper introduces a principled approach for the design of a scalable general reinforcement learning agent. This approach is based on a direct approximation of AIXI, a Bayesian...
AAAI
2006
13 years 10 months ago
2006
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
CORR
2010
Springer
13 years 9 months ago
2010
Springer
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
ATAL
2009
Springer
14 years 3 months ago
2009
Springer
This paper introduces a new model, i.e. state-coupled replicator dynamics, expanding the link between evolutionary game theory and multiagent reinforcement learning to multistate ...