Non prioritized answer set revision

Logic programming, knowledge representation, and nonmonotonic reasoning, 2011

In recent years, numerous papers have shown the power and flexibility of answer set programming (ASP) in the modeling of intelligent agents. This is not surprising since ASP was developed specifically for non-monotonic reasoning-including common-sense reasoning required in agent modeling. When dealing with multiple agents exchanging information, a common problem is dealing with conflicting information. As with humans, our intelligent agents may trust information from some agents more and than from others. In ...

2010

Abstract One of the most challenging aspects of reasoning, planning, and acting in a multi-agent domain is reasoning about what the agents know about the knowledge of their fellows, and to take it into account when planning and acting. In the past this has been done using modal and dynamic epistemic logics. In this paper we explore the use of answer set programming (ASP), and reasoning about action techniques for this purpose. These approaches present a number of theoretical and practical advantages.

Theory and Practice of Logic Programming, 2010

An approach to the revision of logic programs under the answer set semantics is presented. For programs P and Q, the goal is to determine the answer sets that correspond to the revision of P by Q, denoted P * Q. A fundamental principle of classical (AGM) revision, and the one that guides the approach here, is the success postulate. In AGM revision, this stipulates that α ∈ K * α. By analogy with the success postulate, for programs P and Q, this means that the answer sets of Q will in some sense be contained in those of P * Q. The essential idea is that for P * Q, a three-valued answer set for Q, consisting of positive and negative literals, is first determined. The positive literals constitute a regular answer set, while the negated literals make up a minimal set of naf literals required to produce the answer set from Q. These literals are propagated to the program P , along with those rules of Q that are not decided by these literals. The approach differs from work in update logic programs in two main respects. First, we ensure that the revising logic program has higher priority, and so we satisfy the success postulate; second, for the preference implicit in a revision P * Q, the program Q as a whole takes precedence over P , unlike update logic programs, since answer sets of Q are propagated to P . We show that a core group of the AGM postulates are satisfied, as are the postulates that have been proposed for update logic programs.

2004

Abstract We present systems of logic programming agents (LPAS) to model the interactions between decision-makers while evolving to a conclusion. Such a system consists of a number of agents connected by means of unidirectional communication channels. Agents communicate with each other by passing answer sets obtained by updating the information received from connected agents with their own private information. We introduce a credulous answer set semantics for logic programming agents.

Logic Programming and …, 2003

Theory and Practice of Logic Programming, 2007

We have studied the update operator1defined for update sequences by Eiteret al. without tautologies and we have observed that it satisfies an interesting property. This property, which we call Weak Independence of Syntax (WIS), is similar to one of the postulates proposed by Alchourrón, Gärdenfors, and Makinson (AGM); only that in this case it applies to nonmonotonic logic. In addition, we consider other five additional basic properties about update programs and we show that1satisfies them. This work continues the analysis of the AGM postulates with respect to the1operator under a refined view that considersN2as a monotonic logic which allows us to expand our understanding of answer sets. Moreover,N2helped us to derive an alternative definition of1avoiding the use of unnecessary extra atoms.

Artificial Intelligence, 2002

We present different constructions for non-prioritized belief revision, that is, belief changes in which the input sentences are not always accepted. First, we present the concept of explanation in a deductive way. Second, we define multiple revision operators with respect to sets of sentences (representing explanations), giving representation theorems. Finally, we relate the formulated operators with argumentative systems and default reasoning frameworks.

In modeling the knowledge processing structure of an Agent in a Multi-Agent world it becomes necessary to enlarge the traditional concept of Belief Revision. For detecting contradictions and identifying their sources it is sufficient to maintain informations about what has been told; but to "solve" a contradiction it is necessary to keep informations about who said it or, in general, about the source where that knowledge came from. We can take as certain the fact that an agent gave an information, but we can take the given information only as a revisable assumption. The Belief Revision system can't leave the sources of the informations out of consideration because of their relevance in giving the additional notion of "strength of belief" [Galliers 89]. In fact, the reliability of the source affects the credibility of the information and vice-versa. It is necessary to develop systems that deal with couples <assumption, source of the assumption>. In [Dragoni 91] we've proposed a system that moves in this direction. Here we give a short description of that system. In the first two parts we describe the agent's knowledge processing structure using a particular characterization of the "Assumption Based Belief Revision" concept; in part three we outline the project of an embedded device that enables the overall system to deal with couples <assumption, source of the assumption> in an rather anthropomorphic manner.

ACM Sigois Bulletin, 1992

In modeling the knowledge processing structure of an Agent in a Multi-Agent world it becomes necessary to enlarge the traditional concept of Belief Revision. For detecting contradictions and identifying their sources it is sufficient to maintain informations about what has been told; but to "solve" a contradiction it is necessary to keep informations about who said it or, in general, about the source where that knowledge came from. We can take as certain the fact that an agent gave an information, but we can take the given information only as a revisable assumption. The Belief Revision system can't leave the sources of the informations out of consideration because of their relevance in giving the additional notion of "strength of belief" [Galliers 89]. In fact, the reliability of the source affects the credibility of the information and vice-versa. It is necessary to develop systems that deal with couples <assumption, source of the assumption>. In [Dragoni 91] we've proposed a system that moves in this direction. Here we give a short description of that system. In the first two parts we describe the agent's knowledge processing structure using a particular characterization of the "Assumption Based Belief Revision" concept; in part three we outline the project of an embedded device that enables the overall system to deal with couples <assumption, source of the assumption> in an rather anthropomorphic manner.

arXiv (Cornell University), 2016

Belief revision has been studied mainly with respect to background logics that are monotonic in character. In this paper we study belief revision when the underlying logic is nonmonotonic instead-an inherently interesting problem that is under explored. In particular, we will focus on the revision of a body of beliefs that is represented as a logic program under the answer set semantics, while the new information is also similarly represented as a logic program. Our approach is driven by the observation that unlike in a monotonic setting where, when necessary, consistency in a revised body of beliefs is maintained by jettisoning some old beliefs, in a nonmonotonic setting consistency can be restored by adding new beliefs as well. We will define a syntactic revision function and subsequently provide representation theorem for characterising it.