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» Online Testing with Reinforcement Learning
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AGENTS
1999
Springer
14 years 2 months ago
Team-Partitioned, Opaque-Transition Reinforcement Learning
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...
Peter Stone, Manuela M. Veloso
CAINE
2008
13 years 11 months ago
Scripted Artificially Intelligent Basic Online Tactical Simulation
For many years, introductory Computer Science courses have followed the same teaching paradigms. These paradigms utilize only simple console windows; more interactive approaches t...
Jesse D. Phillips, Roger V. Hoang, Joseph D. Mahsm...
ECML
2004
Springer
14 years 3 months ago
Experiments in Value Function Approximation with Sparse Support Vector Regression
Abstract. We present first experiments using Support Vector Regression as function approximator for an on-line, sarsa-like reinforcement learner. To overcome the batch nature of S...
Tobias Jung, Thomas Uthmann
ICML
2003
IEEE
14 years 10 months ago
Testing Exchangeability On-Line
The majority of theoretical work in machine learning is done under the assumption of exchangeability: essentially, it is assumed that the examples are generated from the same prob...
Vladimir Vovk, Ilia Nouretdinov, Alexander Gammerm...
ECML
2006
Springer
14 years 1 months ago
Task-Driven Discretization of the Joint Space of Visual Percepts and Continuous Actions
We target the problem of closed-loop learning of control policies that map visual percepts to continuous actions. Our algorithm, called Reinforcement Learning of Joint Classes (RLJ...
Sébastien Jodogne, Justus H. Piater