Decision-Making Model for Robots that Consider Group Norms and Interests

Fuse, Yotaro; Ashida, Biina; Ayedoun, Emmanuel; Tokumaru, Masataka

doi:10.1007/978-3-031-05409-9_35

Cited by 2 publications

(3 citation statements)

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“…The counterparties of P p are P l and P r , and player P p receives the offered amount m →p (= m r ) and the response r →p (= r l ) from the other players. Thus, the interactions in which player P p is directly involved can be represented as a set T p using the expression (10).…”

Section: Internal Statementioning

confidence: 99%

“…When the agent updated the internal state of a player P p , the interactions observed by player P p in (10) were used to assign a set of the player's observable interactions {P p , P r }, as shown in Fig. 10, to the set P of reward functions in ( 12) and ( 14).…”

Section: ) Renew Estimated State Of Others Spmentioning

confidence: 99%

“…This study requires the agent to exhibit group behavior in more complex scenarios than those in our previous studies. For instance, in one of our earlier studies [10], we merely observed agents' behavior using the proposed model in complex scenarios where the mentioned behavior was required. In contrast, the current study evaluates the agent's ability to adjust to implicit group norms within groups and investigates how the agent's decisions influence human group members.…”

Section: Introductionmentioning

confidence: 99%

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Unleashing Fairness: How a Group Norm-Aware Agent Shakes Up the Ultimatum Game

et al. 2023

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The emergence of social robots has created new opportunities for them to coexist with humans, but only if they can imitate human-like social behavior. Previous research has examined various robot social cues, such as emotions, gestures, and eye contact. However, an area that has been underresearched is the concept of implicit group norms, which are unwritten rules dictating the expected behavior of group members and can differ across different groups. By improving the ability of robots to behave in expected ways, we hope to promote greater acceptance of robots among humans. In this study, we propose a group norm-aware decision-making model to help robots adapt to group norms, which we evaluated in a human-agent experiment based on the ultimatum game. In this scenario, the gains and losses of one group member affect everyone else. Our results demonstrate that a group norm-aware decision-making agent promotes fairer distributions of benefits among group members, enhancing mutual benefit compared with an agent that does not consider group norms. This study provides a solid foundation for further research in developing social robots that are more adaptable and acceptable to humans. Additionally, our proposed model sets the stage for future robot experiments, ultimately leading to the emergence of more equitable and empathetic human-robot interactions.INDEX TERMS Fairness, group norm, human-agent interaction, human-robot interaction, interactive reinforcement learning, social robot, ultimatum game.

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Section: Internal Statementioning

confidence: 99%

Section: ) Renew Estimated State Of Others Spmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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