10.1016/j.cogsys.2026.101480">
 

Cognitive team models in press Diplomacy

Document Type

Article

Publication Date

6-6-2026

Abstract

In general sum multi-player competitive game theory, players dynamically form and disband coalitions as they identify joint utility. However, human players can invalidate this assumption by biasing strategies with emotions and perceptions. This paper shows how machine agents can leverage a perceptual and interpretive team cognitive model to capture these biases and adapt their action strategies. Opponents are represented as non-cooperative team members and the problem is recharacterized as a general sum, multi-player game with imperfect information over player intentions. Agent performance is analyzed via qualitative and quantitative methods in the game of Diplomacy. The results demonstrate that these agents can form cognitive representations of other players that encode elements of structural, perceptual, and interpretive emergence. Additionally, the results suggest that these cognitive representations construct a causal thread throughout game play, that provide intent projections about other players when joining or defecting from coalitions.

Comments

This work was published online as an article of Cognitive Systems Research in June 2026 ahead of inclusion in the September 2026-dated issue cited on this page.

The full article is available from the publisher via subscription or purchase, using the DOI link on this page.

Source Publication

Cognitive Systems Research

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