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CORR
2011
Springer
136views Education» more  CORR 2011»
12 years 9 months ago
Reinforcement Learning for Agents with Many Sensors and Actuators Acting in Categorizable Environments
In this paper, we confront the problem of applying reinforcement learning to agents that perceive the environment through many sensors and that can perform parallel actions using ...
Enric Celaya, Josep M. Porta
ATAL
2006
Springer
13 years 9 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 7 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
ILP
2000
Springer
13 years 9 months ago
Using ILP to Improve Planning in Hierarchical Reinforcement Learning
Hierarchical reinforcement learning has been proposed as a solution to the problem of scaling up reinforcement learning. The RLTOPs Hierarchical Reinforcement Learning System is an...
Mark D. Reid, Malcolm R. K. Ryan
WSC
2007
13 years 8 months ago
Optimizing time warp simulation with reinforcement learning techniques
Adaptive Time Warp protocols in the literature are usually based on a pre-defined analytic model of the system, expressed as a closed form function that maps system state to cont...
Jun Wang, Carl Tropper