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ALDT
2009
Springer
207views Algorithms» more  ALDT 2009»
14 years 2 months ago
Anytime Self-play Learning to Satisfy Functional Optimality Criteria
We present an anytime multiagent learning approach to satisfy any given optimality criterion in repeated game self-play. Our approach is opposed to classical learning approaches fo...
Andriy Burkov, Brahim Chaib-draa
ESANN
2006
13 years 9 months ago
A multiagent architecture for concurrent reinforcement learning
In this paper we propose a multiagent architecture for implementing concurrent reinforcement learning, an approach where several agents, sharing the same environment, perceptions ...
Victor Uc Cetina
ICML
2007
IEEE
14 years 8 months ago
Cross-domain transfer for reinforcement learning
A typical goal for transfer learning algorithms is to utilize knowledge gained in a source task to learn a target task faster. Recently introduced transfer methods in reinforcemen...
Matthew E. Taylor, Peter Stone
NIPS
1994
13 years 9 months ago
Phase-Space Learning
In this paper, we present an improved version of the online phase-space learning algorithm of Tsung and Cottrell (1995), called ARTISTE (Autonomous Real-TIme Selection of Training...
Fu-Sheng Tsung, Garrison W. Cottrell
ICMLA
2010
13 years 5 months ago
Multi-Agent Inverse Reinforcement Learning
Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...
Sriraam Natarajan, Gautam Kunapuli, Kshitij Judah,...