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In this study, we explore the emergence of symbols during interactionsbetween individuals through an experimental semiotic study. Previous studiesinvestigate how humans organize symbol systems through communication usingartificially designed subjective experiments. In this study, we have focused ona joint attention-naming game (JA-NG) in which participants independentlycategorize objects and assign names while assuming their joint attention.  In the theory of the Metropolis-Hastings naming game (MHNG), listeners acceptprovided names according to the acceptance probability computed using theMetropolis-Hastings (MH) algorithm. The theory of MHNG suggests that symbolsemerge as an approximate decentralized Bayesian inference of signs, which isrepresented as a shared prior variable if the conditions of MHNG are satisfied.  This study examines whether human participants exhibit behavior consistentwith MHNG theory when playing JA-NG. By comparing human acceptance decisions ofa partner's naming with acceptance probabilities computed in the MHNG, wetested whether human behavior is consistent with the MHNG theory. The maincontributions of this study are twofold. First, we reject the null hypothesisthat humans make acceptance judgments with a constant probability, regardlessof the acceptance probability calculated by the MH algorithm. This resultsuggests that people followed the acceptance probability computed by the MHalgorithm to some extent. Second, the MH-based model predicted humanacceptance/rejection behavior more accurately than the other four models:Constant, Numerator, Subtraction, and Binary. This result indicates that symbolemergence in JA-NG can be explained using MHNG and is considered an approximatedecentralized Bayesian inference.

Metropolis-Hastings algorithm in joint-attention naming game: Experimental semiotics study