Journal of Computer and System Sciences
A guide to completeness and complexity for modal logics of knowledge and belief
Artificial Intelligence
Reasoning about knowledge
Knowledge compilation and theory approximation
Journal of the ACM (JACM)
Tractable Reasoning in Artificial Intelligence
Tractable Reasoning in Artificial Intelligence
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Dynamic Logic
Fundamenta Informaticae
Complexity of a theory of collective attitudes in teamwork
IAT '05 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Knowledge Representation Techniques (Studies in Fuzziness and Soft Computing)
Knowledge Representation Techniques (Studies in Fuzziness and Soft Computing)
Rational Teams: Logical Aspects of Multi-Agent Systems
Fundamenta Informaticae - Multiagent Systems (FAMAS'03)
On evaluating decision procedures for modal logic
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Computing strongest necessary and weakest sufficient conditions of first-order formulas
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
From Bounded to Unbounded Model Checking for Temporal Epistemic Logic
Fundamenta Informaticae - Multiagent Systems (FAMAS'03)
A Tuning Machine for Cooperative Problem Solving
Fundamenta Informaticae - Multiagent Systems (FAMAS'03)
Evolution of Collective Commitment during Teamwork
Fundamenta Informaticae
Combinations of normal and non-normal modal logics for modeling collective trust in normative MAS
AICOL'11 Proceedings of the 25th IVR Congress conference on AI Approaches to the Complexity of Legal Systems: models and ethical challenges for legal systems, legal language and legal ontologies, argumentation and software agents
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Our previous research presents a methodology of cooperative problem solving for beliefdesire- intention (BDI) systems, based on a complete formal theory called TEAMLOG. This covers both a static part, defining individual, bilateral and collective agent attitudes, and a dynamic part, describing system reconfiguration in a dynamic, unpredictable environment. In this paper, we investigate the complexity of the satisfiability problem of the static part of TEAMLOG, focusing on individual and collective attitudes up to collective intention. Our logics for teamwork are squarely multi-modal, in the sense that different operators are combined and may interfere. One might expect that such a combination is much more complex than the basic multi-agent logic with one operator, but in fact we show that it is not the case: the individual part of TEAMLOG is PSPACE-complete, just like the single modality case. The full system, modelling a subtle interplay between individual and group attitudes, turns out to be EXPTIME-complete, and remains so even when propositional dynamic logic is added to it. Additionally we make a first step towards restricting the language of TEAMLOG in order to reduce its computational complexity. We study formulas with bounded modal depth and show that in case of the individual part of our logics, we obtain a reduction of the complexity to NPTIME-completeness. We also show that for group attitudes in TEAMLOG the satisfiability problem remains in EXPTIMEhard, even when modal depth is bounded by 2. We also study the combination of reducing modal depth and the number of propositional atoms. We show that in both cases this allows for checking the satisfiability in linear time.