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  • The paper considers estimation of Bellman function using revision of the past decisions. The original approach is further extended by employing predictions coming from an imperfect predictor. The resulting algorithm speeds up the convergence of Bellman function estimation and improves the results quality. The potential of the approach is demonstrated on a futures market data.
  • The paper considers estimation of Bellman function using revision of the past decisions. The original approach is further extended by employing predictions coming from an imperfect predictor. The resulting algorithm speeds up the convergence of Bellman function estimation and improves the results quality. The potential of the approach is demonstrated on a futures market data. (en)
Title
  • Ideal and non-ideal predictors in estimation of Bellman function
  • Ideal and non-ideal predictors in estimation of Bellman function (en)
skos:prefLabel
  • Ideal and non-ideal predictors in estimation of Bellman function
  • Ideal and non-ideal predictors in estimation of Bellman function (en)
skos:notation
  • RIV/67985556:_____/11:00368311!RIV12-AV0-67985556
http://linked.open...avai/predkladatel
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  • P(1M0572), P(GA102/08/0567), Z(AV0Z10750506)
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  • 203324
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  • RIV/67985556:_____/11:00368311
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  • Bellman function; estimation; imperfect predictor; futures market data; predictors (en)
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  • [F356304A450B]
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  • Sierra Nevada
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  • Prague
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  • The 2nd International Workshop od Decision Making with Multiple Imperfect Decision Makers. Held in Conjunction with the 25th Annual Conference on Neural Information Processing Systems (NIPS 2011)
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  • Zeman, Jan
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number of pages
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  • Ústav teorie informace a automatizace AV ČR
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  • 978-80-903834-6-3
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