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RESEARCH PRODUCT
On Hagelbarger’s and Shannon’s matching pennies playing machines
Radu CrețulescuMacarie BreazuDaniel MorariuDaniel Volovicisubject
Statement (computer science)Sequencebusiness.industryComputer scienceRobotArtificial intelligenceHidden Markov modelMatching penniesbusinessSoftware implementationdescription
Abstract In the 1950s, Hagelbarger’s Sequence Extrapolating Robot (SEER) and Shannon’s Mind-Reading Machine (MRM) were the state-of-the-art research results in playing the well-known “matching pennies” game. In our research we perform a software implementation for both machines in order to test the common statement that MRM, even simpler, beats SEER. Also, we propose a simple contextual predictor (SCP) and use it to compete with SEER and MRM. As expected, experimental results proves the claimed MRM superiority over SEER and even the SCP’s superiority over both SEER and MRM. At the end, we draw some conclusions and propose further research ideas, like the use of mixing models methods and the use of Hidden Markov Model for modelling player’s behaviour.
year | journal | country | edition | language |
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2020-12-01 | International Journal of Advanced Statistics and IT&C for Economics and Life Sciences |