From conditional commitments to generalized media: on means of coordination between self-governed entities

"In the absence of pre-established coordination structures, what can a self-governed entity – i.e. an entity that chooses on its own between its possible actions and cannot be controlled externally – do to evoke another self-governed entity’s cooperation? In this paper, the motivating conditional self-commitment is conceived to be the basic mechanism to solve coordination problems of this kind. It will be argued that such commitments have an inherent tendency to become more and more generalized and institutionalised. The sociological concept of generalized symbolic media is reinterpreted as a concept that focuses on this point. The conceptual framework resulting from the considerations is applicable to coordination problems between human actors as well as to coordination problems between artificial agents in open multi-agent systems. Thus, it may help to transfer solutions from one realm to the other." (author's abstract)Der Verfasser analysiert die soziale Koordination selbstbestimmter Einheiten unter Bedingungen, unter denen es keine vorher etablierten Koordinationsstrukturen gibt. Er zeigt, dass Engagement der wichtigste Mechanismus zur Lösung von Koordinationsproblemen ist und dass Engagement eine inhärente Tendenz zur Generalisierung und Institutionalisierung aufweist. Der Verfasser stellt einen theoretischen Rahmen vor, der auf einer Neuinterpretation des soziologischen Konzepts verallgemeinerter symbolischer Medien basiert. Dieser Rahmen lässt sich auf Koordinationsprobleme zwischen menschlichen Akteuren ebenso anwenden wie auf Koordinationsprobleme zwischen künstlichen Akteuren in offenen Multiakteursystemen, wie der Verfasser am Beispiel "Reputation" zeigt. (ICE

Computational Theory of Mind for Human-Agent Coordination

In everyday life, people often depend on their theory of mind, i.e., their ability to reason about unobservable mental content of others to understand, explain, and predict their behaviour. Many agent-based models have been designed to develop computational theory of mind and analyze its effectiveness in various tasks and settings. However, most existing models are not generic (e.g., only applied in a given setting), not feasible (e.g., require too much information to be processed), or not human-inspired (e.g., do not capture the behavioral heuristics of humans). This hinders their applicability in many settings. Accordingly, we propose a new computational theory of mind, which captures the human decision heuristics of reasoning by abstracting individual beliefs about others. We specifically study computational affinity and show how it can be used in tandem with theory of mind reasoning when designing agent models for human-agent negotiation. We perform two-agent simulations to analyze the role of affinity in getting to agreements when there is a bound on the time to be spent for negotiating. Our results suggest that modeling affinity can ease the negotiation process by decreasing the number of rounds needed for an agreement as well as yield a higher benefit for agents with theory of mind reasoning.</p