949 search results - page 15 / 190 » Can Doxastic Agents Learn |
MA
1999
Springer
13 years 11 months ago
1999
Springer
In order to maintain their performance in a dynamic environment, agents may be required to modify their learning behavior during run-time. If an agent utilizes a rule-based system...
AAMAS
2002
Springer
13 years 7 months ago
2002
Springer
In reinforcement learning, an agent tries to learn a policy, i.e., how to select an action in a given state of the environment, so that it maximizes the total amount of reward it ...
AAAI
2011
12 years 7 months ago
2011
We propose CCRank, the first parallel algorithm for learning to rank, targeting simultaneous improvement in learning accuracy and efficiency. CCRank is based on cooperative coev...
ATAL
2008
Springer
13 years 9 months ago
2008
Springer
Effective norms, emerging from sustained individual interactions over time, can complement societal rules and significantly enhance performance of individual agents and agent soci...
ICML
1994
IEEE
13 years 11 months ago
1994
IEEE
In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function....