Informally, in revising k by, we begin with and incorporate as much of k as consistently possible. Belief revision is the process of changing beliefs to take into account a new piece of information. This paper presents a general, consistency based framework for expressing belief change. First, we use a consistencybased approach, which is distinct from any of the revision policies in 9. Delgrande and torsten schaub, consistency based approaches to merging knowledge bases, tenth international workshop on nonmonotonic reasoning nmr2004, whistler, bc, june 2004. An implementation of consistencybased multiagent belief change using asp paul vicol 1, james delgrande, and torsten schaub2 1 simon fraser university burnaby b. Global completion, simple iteration, expanding iteration, augmenting iteration, and.
For belief revision, informally, in revising a knowledge base k by a sentence, we begin with and include as much of k as consistently possible. Citeseerx a consistencybased approach for belief change. A uniform approach to belief revision and belief progression. The present paper explores whether this consistency. Start studying human resources management compensation chapter seven. A computational approach for belief change springerlink. A decomposition based algorithm for maximal contractions. This process of policy learning is consistent if policy preferences are. Formally, a knowledge base k and sentence are expressed, via renaming propositions in k, in separate alphabets, but such that there is an. Classic works of the dempstershafer theory of belief functions.
The spatial consistency of the relative high risk area with past disaster points. The organization wanted a system that provided consistency, fairness, and lasting. A consistencybased approach to knowledge base refinement. Fundamentally, probcons is a pairhidden markov model based progressive alignment algorithm that primarily differs from most typical approaches in its use of maximum expected accuracy rather than viterbi alignment, and of the probabilistic consistency transformation to incorporate multiple sequence conservation information during pairwise alignment. Section 4 presents the general framework, then explores revision and contraction.
Abstract we present a general, consistency based framework for belief change. Consistency between beliefs and behavior regarding use of. Second, we describe a \oneshot method for belief sharing, rather than an iterated method. Human resources management compensation chapter seven. A revision algorithm based on this decomposing function is proposed, which can calculate maximal contractions of a given problem. Informally, in revising k by a, we begin with a and incorporate as much of k as. A consistencybased approach for belief change request pdf. Despite many beliefs it is not a new concept but, in. Compared to the more common serverclient solution, a peertopeer approach has. The existence of a common prior implies trade consistency for such spaces, but the opposite entailment does not hold, as was demonstrated by feinberg 2000. Informally, in revising a knowledge base k by sentence,webegin with k.
An implementation of consistencybased multiagent belief. Perspectives from artificial intelligence, philosophy, and economics, 7. We have presented two approaches for merging belief sets, expressed in a general, consistency based framework for belief change 5. Mapping mountain torrent hazards in the hexi corridor using an. We introduce functions to revise or contract a belief set, as well as functions to revise or contract a belief base. We will make use of the notion of a selection function c that for any set i 6. In this paper we extend a consistency based approach originally introduced by delgrande and schaub to belief revision for structured belief bases.
Equibel is a python package for working with consistency based belief change in a graphoriented setting. In this paper, we combine the syntax based belief change approach and model based approach, and present a computational approach for belief change. In section 3 we discuss intuitions underlying our approach and, in particular, the suitability of a consistency based approach. We present a general, consistency based framework for belief change. James delgrande and torsten schaub, a consistency based approach for belief change, artificial intelligence journal 151, 12, 2003, pp.
The degree of belief for torrent hazard in the hexi corridor. A consistencybased framework for merging knowledge bases. These theories included allegations that climate change is a hoax perpetrated by. A consistencybased approach for belief change computing. Informally, in revising k by a, we begin with a and incorporate as much of k as consistently possible. The framework has good formal properties while being wellsuited for implementation. Read distributed decision support systems under limited degrees of competence. Proceedings of the international conference on agents and artificial intelligence icaart. The framework has good formal properties while being wellsuited. Application of this logicbased approach to problems of knowledge. Belief in this conspiracy theory shapes negative attitudes towards. Consistencybased revision of structured belief bases. Informally, in revising a knowledge base k by sentence. Introducing equibel an implementation of consistency.
A semantic framework for preference handling in answer set programming corr cs. In the first approach, the intuition is that for merging belief. A consistency based approach to knowledge base renement tri m. Formally, a knowledge base k and sentence a are expressed, via renaming propositions in k, in separate languages. Consistencybased approaches to merging knowledge bases. Citeseerx document details isaac councill, lee giles, pradeep teregowda. Abstractthis paper presents a general, consistency based framework for expressing belief change. A simulation study, decision support systems on deepdyve, the largest online rental service for scholarly research with thousands of academic publications available at your fingertips. Consistency between beliefs and behavior regarding use of substances in recovery. Symbolic and quantitative approaches to reasoning with. Request pdf classic works of the dempstershafer theory of belief functions this is a. When expressing the satisfiability of a formula, these literal sets are equivalent to all satisfied models of such formula. This paper presents a general, consistencybased framework for expressing belief change.
We also show properties of the revision functions and the contraction functions. For belief revision, informally, in revising a knowledge base k by a sentence. Consistency based approaches to belief set merging in this section we modify the framework given by definition 2. The consistencybased framework we employ here has been developed in a series of papers, including 1, 2, and 3. Were upgrading the acm dl, and would like your input.
A framework for compiling preferences in logic programs. The approach has something of the same flavour as the consistency based paradigm for diagnosis or the assumption based approach to default reasoning, although it differs significantly in details. I forced compliance, but he will still believe the company was wrong. The central notion is that of a belief change scenario consisting of a triple of sets of formulas, bk,r,c. Syntactic propositional belief bases fusion with removed sets. Propositional knowledge base revision and minimal change. This flexible framework allows for the simultaneous specification of revision, multiple con tractions, together with integrity constraints, with respect to a given knowledge base. Delgrande, torsten schaub, a consistency based approach for belief change, artificial intelligence, v. Abstract this paper presents a general, consistencybased framework for expressing belief change. In this approach, the agm postulates for revision are effectively satis. An algorithm for computing inconsistency measurement by paraconsistent semantics.
The standard bayesian approach, as developed by savage 1954, provides the conditions under which a decision maker whose preferences. We present a general, consistencybased framework for belief change. Equibel is a python package for working with consistency based belief change in a graphoriented setting currently supported platforms. A consistencybased approach for belief change core. Approaches to constructing a stratified merged knowledge base. A consistencybased approach for belief change sciencedirect. There, and here, the central intuition is that for belief change one begins by expressing the various knowledge bases, belief sources, etc. Learn vocabulary, terms, and more with flashcards, games, and other study tools.