Gregory Gelfond

Logic programming for finding models in the logics of knowledge and its applications: A case study

The logics of knowledge are modal logics that have been shown to be effective in representing and reasoning about knowledge in multi-agent domains. Relatively few computational frameworks for dealing with computation of models and useful transformations in logics of knowledge (e.g., to support multi-agent planning with knowledge actions and degrees of visibility) have been proposed. This paper explores the use of logic programming (LP) to encode interesting forms of logics of knowledge and compute Kripke models. The LP modeling is expanded with useful operators on Kripke structures, to support multi-agent planning in the presence of both world-altering and knowledge actions. This results in the first ever implementation of a planner for this type of complex multi-agent domains.

Answer set programming and planning with knowledge and world-altering actions in multiple agent domains

This paper discusses the planning problem in multi-agent domains, in which agents may execute not only world-altering actions, but also epistemic actions. The paper reviews the concepts of Kripke structures and update models, as proposed in the literature to model epistemic and ontic actions; it then discusses the use of Answer Set Programming (ASP) in representing and reasoning about the effects of actions on the world, the knowledge of agents, and planning. The paper introduces the m

On representing actions in multi-agent domains

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Reasoning about the Beliefs of Agents in Multi-agent Domains in the Presence of State Constraints: The Action Language mAL

language, an action language for multi-agent domains with epistemic and ontic actions, to demonstrate the proposed ASP model.

Using answer set programming to model multi-agent scenarios involving agents' knowledge about other's knowledge

Reasoning about actions forms the foundation of prediction, planning, explanation, and diagnosis in a dynamic environment. Most of the research in this field has focused on domains with a single agent, albeit in a dynamic environment, with considerably less attention being paid to multi-agent domains. In a domain with multiple agents, interesting issues arise when one considers the knowledge of various agents about the world, as well about as each others knowledge. This aspect of multi-agent domains has been studied in the field of dynamic epistemic logic. In this paper we review work by Baltag and Moss on multi-agent reasoning in the context of dynamic epistemic logic, extrapolate their work to the case where agents in a domain are classified into three types and suggest directions for combining ideas from dynamic epistemic logic and reasoning about actions and change in order to obtain a unified theory of multi-agent actions.

Textual inference by combining multiple Logic programming paradigms

Reasoning about actions forms the basis of many tasks such as prediction, planning, and diagnosis in a dynamic domain. Within the reasoning about actions community, a broad class of languages called action languages has been developed together with a methodology for their use in representing dynamic domains. With a few notable exceptions, the focus of these efforts has largely centered around single-agent systems. Agents rarely operate in a vacuum however, and almost in parallel, substantial work has been done within the dynamic epistemic logic community towards understanding how the actions of an agent may affect the knowledge and/or beliefs of his fellows. What is less understood by both communities is how to represent and reason about both the direct and indirect effects of both ontic and epistemic actions within a multi-agent setting. This paper presents a new action language, m

An Action Language for Reasoning about Beliefs in Multi-Agent Domains

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Exploring the KD45 n property of a kripke model after the execution of an action sequence

, which brings together techniques developed in both communities for reasoning about dynamic multi-agent domains involving both ontic and epistemic actions, as well as the indirect effects that such actions may have on the domain.