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» Universal Reinforcement Learning
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ICML
1998
IEEE
16 years 15 days ago
The MAXQ Method for Hierarchical Reinforcement Learning
This paper presents a new approach to hierarchical reinforcement learning based on the MAXQ decomposition of the value function. The MAXQ decomposition has both a procedural seman...
Thomas G. Dietterich
CIG
2005
IEEE
15 years 1 months ago
A Survey on Multiagent Reinforcement Learning Towards Multi-Robot Systems
Abstract- Multiagent reinforcement learning for multirobot systems is a challenging issue in both robotics and artificial intelligence. With the ever increasing interests in theor...
Erfu Yang, Dongbing Gu
AAAI
2010
15 years 1 months ago
Reinforcement Learning via AIXI Approximation
This paper introduces a principled approach for the design of a scalable general reinforcement learning agent. This approach is based on a direct approximation of AIXI, a Bayesian...
Joel Veness, Kee Siong Ng, Marcus Hutter, David Si...
IJCAI
2007
15 years 1 months ago
Heuristic Selection of Actions in Multiagent Reinforcement Learning
This work presents a new algorithm, called Heuristically Accelerated Minimax-Q (HAMMQ), that allows the use of heuristics to speed up the wellknown Multiagent Reinforcement Learni...
Reinaldo A. C. Bianchi, Carlos H. C. Ribeiro, Anna...
ACSE
2000
ACM
15 years 4 months ago
The information environments program - a new design based IT degree
The University of Queensland has recently established a new design-focused, studio-based IT degree at a new “flexible-learning” campus. The Bachelor of Information Environment...
Michael Docherty, Peter Sutton, Margot Brereton, S...