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.

Errare humanum est? A pilot study to evaluate the human-likeness of a ai othello playing agent / Lauletta, E.; Biancardi, B.; Norelli, A.; Mancini, M.; Panconesi, A.. - (2022), pp. 1-3. (Intervento presentato al convegno 22nd ACM International Conference on Intelligent Virtual Agents, IVA 2022 tenutosi a Faro) [10.1145/3514197.3549699].

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

Norelli A.;Mancini M.;Panconesi A.
2022

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.
2022
22nd ACM International Conference on Intelligent Virtual Agents, IVA 2022
AI agent; board game; human-likeness; othello
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Errare humanum est? A pilot study to evaluate the human-likeness of a ai othello playing agent / Lauletta, E.; Biancardi, B.; Norelli, A.; Mancini, M.; Panconesi, A.. - (2022), pp. 1-3. (Intervento presentato al convegno 22nd ACM International Conference on Intelligent Virtual Agents, IVA 2022 tenutosi a Faro) [10.1145/3514197.3549699].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1679353
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