171 search results - page 18 / 35 » Principled Methods for Advising Reinforcement Learning Agent... |
AAAI
2000
13 years 9 months ago
2000
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 ...
ICML
2000
IEEE
14 years 8 months ago
2000
IEEE
Stochastic games are a generalization of MDPs to multiple agents, and can be used as a framework for investigating multiagent learning. Hu and Wellman (1998) recently proposed a m...
AGENTS
1999
Springer
13 years 12 months ago
1999
Springer
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
ATAL
2007
Springer
14 years 1 months ago
2007
Springer
Reinforcement learning is a popular and successful framework for many agent-related problems because only limited environmental feedback is necessary for learning. While many algo...
ICCBR
2005
Springer
14 years 1 months ago
2005
Springer
CBR is one of the techniques that can be applied to the task of approximating a function over high-dimensional, continuous spaces. In Reinforcement Learning systems a learning agen...