236 search results - page 32 / 48 » Non-linear dynamics in multiagent reinforcement learning alg... |
AAAI
2000
13 years 9 months ago
2000
As applications for artificially intelligent agents increase in complexity we can no longer rely on clever heuristics and hand-tuned behaviors to develop their programming. Even 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...
ATAL
2009
Springer
14 years 2 months ago
2009
Springer
In large systems, it is important for agents to learn to act effectively, but sophisticated multi-agent learning algorithms generally do not scale. An alternative approach is to ...
NECO
2007
13 years 7 months ago
2007
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
EUROCAST
2007
Springer
14 years 2 months ago
2007
Springer
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...