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» Online Testing with Reinforcement Learning
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AGENTS
1999
Springer
15 years 4 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
15 years 1 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
15 years 5 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
16 years 16 days 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
15 years 3 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