Errare humanum est?: a pilot study to evaluate the human-likeness of a AI othello playing agent

Enrico Lauletta, Béatrice Biancardi, Antonio Norelli, M. Mancini, A. Panconesi
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Abstract

Olivaw is an AI Othello playing agent which autonomously learns how to improve its gameplay by playing against itself. Some top-notch players (including former World Champions) reported that they had the impression that Olivaw's gameplay was human-like. To better investigate the processes related to these impressions, we conducted a pilot study using the Othello Game Evaluation App, a computer application we developed to evaluate pre-recorded Othello games in a controlled setting while assuring an adequate user experience. An exploratory analysis of the results shows that the participants mostly evaluated Olivaw as a human. When asked for a motivation for their choice, some of them reported that they evaluate poor game moves (and, consequently, losing the game) as an indication of the human-likeness of the player.
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错误的人类est?一项初步研究,以评估人工智能奥赛罗的人类相似性
Olivaw是一个AI奥赛罗游戏代理,它可以自主学习如何通过与自己对抗来提高游戏玩法。一些顶级玩家(包括前世界冠军)表示,他们觉得《Olivaw》的玩法和人类很像。为了更好地调查与这些印象相关的过程,我们使用奥赛罗游戏评估应用程序进行了一项试点研究,这是我们开发的一款计算机应用程序,用于在受控环境下评估预先录制的奥赛罗游戏,同时确保充分的用户体验。对结果的探索性分析表明,参与者大多将奥利瓦视为人类。当被问及做出选择的动机时,有些人表示他们会将糟糕的游戏移动(并因此输掉游戏)视为玩家与人类相似的迹象。
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