Strategic and private reasoning with the concurrent (timed) language for argumentation

Abstract Modelling the interactions and reasoning processes of multiple agents in a dynamic environment presents a significant challenge, requiring tools that effectively capture diverse interaction types (such as persuasion and deliberation) while supporting agents in decision-making and consensus-building. We extend the Timed Concurrent Language For Argumentation (TCLA) to support the specification of agents equipped with local argument memories and private knowledge reasoning. This extension enables the full formalization of Symmetric Strategic Argumentation Dialogues and Multi-Agent Decision Making with Privacy Preserved problems within TCLA, for which we also introduce general translation functions to automatically obtain TCLA programs. To demonstrate practical applications of TCLA, we provide examples that model the two studied problems and make use of the translation functions.