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MAGS
2010
81views more  MAGS 2010»
15 years 1 months ago
Task allocation learning in a multiagent environment: Application to the RoboCupRescue simulation
Coordinating agents in a complex environment is a hard problem, but it can become even harder when certain characteristics of the tasks, like the required number of agents, are un...
Sébastien Paquet, Brahim Chaib-draa, Patric...
AAAI
2011
14 years 6 months ago
CCRank: Parallel Learning to Rank with Cooperative Coevolution
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...
Shuaiqiang Wang, Byron J. Gao, Ke Wang, Hady Wiraw...
ECTEL
2007
Springer
16 years 24 days ago
Creation of Lithuanian Digital Library of Educational Resources and Services: the Hypothesis, Contemporary Practice, and Future
Currently national digital library of educational resources and services (DLE) for primary and secondary education is under implementation in Lithuania. The article aims to analyse...
Eugenijus Kurilovas, Svetlana Kubilinskiene
HICSS
2003
IEEE
116views Biometrics» more  HICSS 2003»
15 years 12 months ago
Modeling Instrumental Conditioning - The Behavioral Regulation Approach
Basically, instrumental conditioning is learning through consequences: Behavior that produces positive results (high “instrumental response”) is reinforced, and that which pro...
Jose J. Gonzalez, Agata Sawicka
ATAL
2010
Springer
15 years 7 months ago
Frequency adjusted multi-agent Q-learning
Multi-agent learning is a crucial method to control or find solutions for systems, in which more than one entity needs to be adaptive. In today's interconnected world, such s...
Michael Kaisers, Karl Tuyls