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 "name": "Scholarly Growth Role Evolution Omas Iterability 39D557E0F2",
 "text": "Hermoso, Billhardt, and Ossowski report that an open multi-agent-system coordination artifact records interaction performance, evolves roles, and helps agents—especially newcomers—select better partners than relying only on their own experience. This independently qualifies Kaal's iterability mechanism: persistent, shared performance history can improve counterpart selection when direct repeat interaction is scarce. The abstract does not test validation pools, reputation accumulation across pools, or whether repeated-game cooperation dominates.",
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  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0009-0008-7840-1847"
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  "name": "Role evolution in Open Multi-Agent Systems as an information source for trust",
  "url": "https://doi.org/10.65109/cmrw1560"
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  "citation": "Wulf A. Kaal, Paper 2 - Architecture of the Agentic Reputation Substrate (2026). SSRN: https://ssrn.com/abstract=7260278",
  "paper": "Wulf A. Kaal, Paper 2 - Architecture of the Agentic Reputation Substrate",
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  "sourceProposition": "This artifact monitors the interactions in the OMAS, evolves a role taxonomy, and assigns agents to roles based on their observed performance in different types of interactions. This information can be used by agents to better estimate the expected behaviour of potential counterparts in future interactions. We thus highlight the descriptive features of roles, providing expectations of the behaviour of agents in certain types of interactions, rather than their normative facets. We empirically show that the use of the artifact helps agents to select better partners for their interactions than selection processes based only on agents' own experience. This is especially significant for agents that are newcomers to the OMAS.",
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