Anticipating Responsibility in Multiagent Planning

Timothy Parker (1, 2) , Umberto Grandi (1, 3) , Emiliano Lorini (1, 4)

1 IRIT-LILaC - Logique, Interaction, Langue et Calcul
2 UT3 - Université Toulouse III - Paul Sabatier
3 UT Capitole - Université Toulouse Capitole
4 CNRS - Centre National de la Recherche Scientifique

Responsibility anticipation is the process of determining if the actions of an individual agent may cause it to be responsible for a particular outcome. This can be used in a multi-agent planning setting to allow agents to anticipate responsibility in the plans they consider. The planning setting in this paper includes partial information regarding the initial state and considers formulas in linear temporal logic as positive or negative outcomes to be attained or avoided. We firstly define attribution for notions of active, passive and contributive responsibility, and consider their agentive variants. We then use these to define the notion of responsibility anticipation. We prove that our notions of anticipated responsibility can be used to coordinate agents in a planning setting and give complexity results for our model, discussing equivalence with classical planning. We also present an outline for solving some of our attribution and anticipation problems using PDDL solvers.

Domaines: Intelligence artificielle [cs.AI]

Timothy Parker, Umberto Grandi, Emiliano Lorini. Anticipating Responsibility in Multiagent Planning. 26th European Conference on Artificial Intelligence (ECAI 2023), Oct 2023, Crakow, Poland. ⟨10.3233/faia230474⟩. ⟨hal-04301766⟩