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IEAAIE
2001
Springer
13 years 12 months ago
On the Relationship between Learning Capability and the Boltzmann-Formula
In this paper a combined use of reinforcement learning and simulated annealing is treated. Most of the simulated annealing methods suggest using heuristic temperature bounds as the...
Péter Stefán, Laszlo Monostori
ECML
2005
Springer
14 years 1 months ago
Towards Finite-Sample Convergence of Direct Reinforcement Learning
Abstract. While direct, model-free reinforcement learning often performs better than model-based approaches in practice, only the latter have yet supported theoretical guarantees f...
Shiau Hong Lim, Gerald DeJong
ATAL
2006
Springer
13 years 11 months ago
Rule value reinforcement learning for cognitive agents
RVRL (Rule Value Reinforcement Learning) is a new algorithm which extends an existing learning framework that models the environment of a situated agent using a probabilistic rule...
Christopher Child, Kostas Stathis
NIPS
1992
13 years 8 months ago
Feudal Reinforcement Learning
This paper describes the adaption and application of an algorithm called Feudal Reinforcement Learning to a complex gridworld navigation problem. The algorithm proved to be not ea...
Peter Dayan, Geoffrey E. Hinton
SIGIR
2003
ACM
14 years 24 days ago
ReCoM: reinforcement clustering of multi-type interrelated data objects
Most existing clustering algorithms cluster highly related data objects such as Web pages and Web users separately. The interrelation among different types of data objects is eith...
Jidong Wang, Hua-Jun Zeng, Zheng Chen, Hongjun Lu,...