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ATAL
2007
Springer
14 years 1 months ago
Theoretical advantages of lenient Q-learners: an evolutionary game theoretic perspective
This paper presents the dynamics of multiple reinforcement learning agents from an Evolutionary Game Theoretic (EGT) perspective. We provide a Replicator Dynamics model for tradit...
Liviu Panait, Karl Tuyls
AAAI
2000
13 years 8 months ago
Localizing Search in Reinforcement Learning
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...
Gregory Z. Grudic, Lyle H. Ungar
IAT
2005
IEEE
14 years 1 months ago
Self-Organizing Cognitive Agents and Reinforcement Learning in Multi-Agent Environment
This paper presents a self-organizing cognitive architecture, known as TD-FALCON, that learns to function through its interaction with the environment. TD-FALCON learns the value ...
Ah-Hwee Tan, Dan Xiao
ICML
2006
IEEE
14 years 8 months ago
Qualitative reinforcement learning
When the transition probabilities and rewards of a Markov Decision Process are specified exactly, the problem can be solved without any interaction with the environment. When no s...
Arkady Epshteyn, Gerald DeJong
ESANN
2003
13 years 8 months ago
Improving iterative repair strategies for scheduling with the SVM
The resource constraint project scheduling problem (RCPSP) is an NP-hard benchmark problem in scheduling which takes into account the limitation of resources’ availabilities in ...
Kai Gersmann, Barbara Hammer