Anticipating Responsibility in Multiagent Planning - Intelligence Artificielle Access content directly
Conference Papers Year : 2023

Anticipating Responsibility in Multiagent Planning

Abstract

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.
Fichier principal
Vignette du fichier
FAIA-372-FAIA230474.pdf (351.48 Ko) Télécharger le fichier
Origin : Publisher files allowed on an open archive

Dates and versions

hal-04301766 , version 1 (23-11-2023)

Licence

Attribution - NonCommercial

Identifiers

Cite

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⟩
84 View
7 Download

Altmetric

Share

Gmail Facebook X LinkedIn More