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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2509.24660 |
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| _version_ | 1866912615012237312 |
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| author | Kondylidis, Nikolaos Yaman, Anil van Harmelen, Frank Acar, Erman Teije, Annette ten |
| author_facet | Kondylidis, Nikolaos Yaman, Anil van Harmelen, Frank Acar, Erman Teije, Annette ten |
| contents | The main approach to evaluating communication is by assessing how well it facilitates coordination. If two or more individuals can coordinate through communication, it is generally assumed that they understand one another. We investigate this assumption in a signaling game where individuals develop a new vocabulary of signals to coordinate successfully. In our game, the individuals do not have common observations besides the communication signal and outcome of the interaction, i.e. received reward. This setting is used as a proxy to study communication emergence in populations of agents that perceive their environment very differently, e.g. hybrid populations that include humans and artificial agents. Agents develop signals, use them, and refine interpretations while not observing how other agents are using them. While populations always converge to optimal levels of coordination, in some cases, interacting agents interpret and use signals differently, converging to what we call successful misunderstandings. However, agents of population that coordinate using misaligned interpretations, are unable to establish successful coordination with new interaction partners. Not leading to coordination failure immediately, successful misunderstandings are difficult to spot and repair. Having at least three agents that all interact with each other are the two minimum conditions to ensure the emergence of shared interpretations. Under these conditions, the agent population exhibits this emergent property of compensating for the lack of shared observations of signal use, ensuring the emergence of shared interpretations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_24660 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Successful Misunderstandings: Learning to Coordinate Without Being Understood Kondylidis, Nikolaos Yaman, Anil van Harmelen, Frank Acar, Erman Teije, Annette ten Artificial Intelligence The main approach to evaluating communication is by assessing how well it facilitates coordination. If two or more individuals can coordinate through communication, it is generally assumed that they understand one another. We investigate this assumption in a signaling game where individuals develop a new vocabulary of signals to coordinate successfully. In our game, the individuals do not have common observations besides the communication signal and outcome of the interaction, i.e. received reward. This setting is used as a proxy to study communication emergence in populations of agents that perceive their environment very differently, e.g. hybrid populations that include humans and artificial agents. Agents develop signals, use them, and refine interpretations while not observing how other agents are using them. While populations always converge to optimal levels of coordination, in some cases, interacting agents interpret and use signals differently, converging to what we call successful misunderstandings. However, agents of population that coordinate using misaligned interpretations, are unable to establish successful coordination with new interaction partners. Not leading to coordination failure immediately, successful misunderstandings are difficult to spot and repair. Having at least three agents that all interact with each other are the two minimum conditions to ensure the emergence of shared interpretations. Under these conditions, the agent population exhibits this emergent property of compensating for the lack of shared observations of signal use, ensuring the emergence of shared interpretations. |
| title | Successful Misunderstandings: Learning to Coordinate Without Being Understood |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2509.24660 |