Modelling Control Arguments via Cooperation Logic in Unforeseen Scenarios
This work addresses a gap in multi-agent systems for AI researchers, but it appears incremental as it builds on existing control argumentation frameworks.
The paper tackled the problem of modeling coalition formation and interactions among multiple agents in uncertain environments, which existing control argumentation frameworks inadequately address, by proposing a formalism using cooperation logic to investigate agents' strategies and actions in dynamic scenarios.
The intent of control argumentation frameworks is to specifically model strategic scenarios from the perspective of an agent by extending the standard model of argumentation framework in a way that takes unquantified uncertainty regarding arguments and attacks into account. They do not, however, adequately account for coalition formation and interactions among a set of agents in an uncertain environment. To address this challenge, we propose a formalism of a multi-agent scenario via cooperation logic and investigate agents' strategies and actions in a dynamic environment.