On Hagelbarger’s and Shannon’s matching pennies playing machines

Breazu Macarie (), Volovici Daniel (), Morariu Daniel I. () and Crețulescu Radu G. ()
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Breazu Macarie: Computer Science and Electrical and Electronics Engineering Department, Faculty of Engineering, “Lucian Blaga” University of Sibiu, Romania
Volovici Daniel: Computer Science and Electrical and Electronics Engineering Department, Faculty of Engineering, “Lucian Blaga” University of Sibiu, Romania
Morariu Daniel I.: Computer Science and Electrical and Electronics Engineering Department, Faculty of Engineering, “Lucian Blaga” University of Sibiu, Romania
Crețulescu Radu G.: Computer Science and Electrical and Electronics Engineering Department, Faculty of Engineering, “Lucian Blaga” University of Sibiu, Romania

International Journal of Advanced Statistics and IT&C for Economics and Life Sciences, 2020, vol. 10, issue 1, 56-66

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.

Keywords: matching pennies; Hagelbarger; sequence extrapolating robot; Shannon; mind reading machine; contextual predictor (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:ijsiel:v:10:y:2020:i:1:p:56-66:n:5

DOI: 10.2478/ijasitels-2020-0003

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