publication . Article . Other literature type . 2014

The Reinforcement Learning Competition 2014

Christos Dimitrakakis; Guangliang Li; Nikoalos Tziortziotis;
Open Access
  • Published: 19 Sep 2014 Journal: AI Magazine, volume 35, pages 61-65 (issn: 0738-4602, eissn: 2371-9621, Copyright policy)
  • Publisher: Association for the Advancement of Artificial Intelligence (AAAI)
  • Country: Netherlands
Abstract
<jats:p>Reinforcement learning is one of the most general problems in artificial intelligence. It has been used to model problems in automated experiment design, control, economics, game playing, scheduling and telecommunications. The aim of the reinforcement learning competition is to encourage the development of very general learning agents for arbitrary reinforcement learning problems and to provide a test-bed for the unbiased evaluation of algorithms.</jats:p>
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free text keywords: Artificial Intelligence, Scheduling (computing), Learning classifier system, Active learning (machine learning), Reinforcement learning, Machine learning, computer.software_genre, computer, business.industry, business, Robot learning, Computer science, Error-driven learning, Game playing, Hyper-heuristic
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Article . 2014
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Other literature type . 2014
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