"Teammates, Am I Clear?": Analysing Legible Behaviours in Teams
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866918107066400768 |
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| author | Faria, Miguel Melo, Francisco S. Paiva, Ana |
| author_facet | Faria, Miguel Melo, Francisco S. Paiva, Ana |
| contents | In this paper we investigate the notion of legibility in sequential decision-making in the context of teams and teamwork. There have been works that extend the notion of legibility to sequential decision making, for deterministic and for stochastic scenarios. However, these works focus on one agent interacting with one human, foregoing the benefits of having legible decision making in teams of agents or in team configurations with humans. In this work we propose an extension of legible decision-making to multi-agent settings that improves the performance of agents working in collaboration. We showcase the performance of legible decision making in team scenarios using our proposed extension in multi-agent benchmark scenarios. We show that a team with a legible agent is able to outperform a team composed solely of agents with standard optimal behaviour. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_21631 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | "Teammates, Am I Clear?": Analysing Legible Behaviours in Teams Faria, Miguel Melo, Francisco S. Paiva, Ana Artificial Intelligence Multiagent Systems In this paper we investigate the notion of legibility in sequential decision-making in the context of teams and teamwork. There have been works that extend the notion of legibility to sequential decision making, for deterministic and for stochastic scenarios. However, these works focus on one agent interacting with one human, foregoing the benefits of having legible decision making in teams of agents or in team configurations with humans. In this work we propose an extension of legible decision-making to multi-agent settings that improves the performance of agents working in collaboration. We showcase the performance of legible decision making in team scenarios using our proposed extension in multi-agent benchmark scenarios. We show that a team with a legible agent is able to outperform a team composed solely of agents with standard optimal behaviour. |
| title | "Teammates, Am I Clear?": Analysing Legible Behaviours in Teams |
| topic | Artificial Intelligence Multiagent Systems |
| url | https://arxiv.org/abs/2507.21631 |