Dynamic Epistemic Logic of Resource Bounded Information Mining Agents

Publication date

2024-05

Authors

Dolgorukov, Vitaliy
Galimullin, Rustam
Gladyshev, MaksimORCID 0000-0002-6657-4870ISNI 0000000523483460

Editors

Advisors

Supervisors

DOI

Document Type

/dk/atira/pure/researchoutput/researchoutputtypes/contributiontojournal/conferencearticle

Collections

Open Access logo

License

cc_by

Abstract

Logics for resource-bounded agents have been getting more and more attention in recent years since they provide us with more realistic tools for modelling and reasoning about multi-agent systems. While many existing approaches are based on the idea of agents as imperfect reasoners, who must spend their resources to perform logical inference, this is not the only way to introduce resource constraints into logical settings. In this paper we study agents as perfect reasoners, who may purchase a new piece of information from a trustworthy source. For this purpose we propose dynamic epistemic logic for semi-public queries for resource-bounded agents. In this logic (groups of) agents can perform a query (ask a question) about whether some formula is true and receive a correct answer. These queries are called semi-public, because the very fact of the query is public, while the answer is private. We also assume that every query has a cost and every agent has a budget constraint. Finally, our framework allows us to reason about group queries, in which agents may share resources to obtain a new piece of information together. We demonstrate that our logic is complete, decidable and has an efficient model checking procedure.

Keywords

Common Knowledge, Dynamic Epistemic Logic, Epistemic Logic, Group Queries, Resource Bounded Agents, Artificial Intelligence, Software, Control and Systems Engineering

Citation

Dolgorukov, V, Galimullin, R & Gladyshev, M 2024, 'Dynamic Epistemic Logic of Resource Bounded Information Mining Agents', Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, vol. 2024, no. May, pp. 481-489.