Dealing Automatically with Exceptions by Introducing Specificity in ASP

Answer Set Programming (ASP), via normal logic programs, is known as a suitable framework for default reasoning since it offers both a valid formal model and operational systems. However, in front of a real world knowledge representation problem, it is not easy to represent information in this framework. That is why the present article proposed to deal with this issue by generating in an automatic way the suitable normal logic program from a compact representation of the information. This is done by using a method, based on specificity, that has been developed for default logic and which is adapted here to ASP both in theoretical and practical points of view

Logical handling of uncertain, ontology-based, spatial information

The paper describes a logical framework for handling uncertain spatial information, and merging it when it comes from multiple sources. For this purpose, we use a simple logical formalization for spatial ontologies and for property ontologies relative to different universes of discourse (these ontologies only involve subsumption and mutual exclusiveness relations), since spatial information typically associates properties to sets of parcels that are themselves described in terms of the spatial and/or property vocabularies appearing in the ontologies. Apart from the ontological information describing relations between vocabulary labels, we propose to represent a piece of spatial information as a pair, called "attributive formula", associating a property formula to a set of parcels (represented by a spatial formula). A set of inference rules is given in order to be able to reason from these attributive pairs. Then, we examine how uncertainty can be encoded in attributive information, using possibilistic logic in a reified manner with respect to parcels. Another important issue pointed out in this paper is that there are two ways to link a property to an area. A first meaning is that the property is true everywhere in the area, a second meaning is that the property is at least true somewhere in the area. This distinction is necessary in order to be able to use both ontological information (which can be encoded by "everywhere" attributive-formulas) and attributive information (which contain the two kinds of attributive-formulas). Lastly, the paper studies how information fusion problems can be handled in the context of spatial data. The problems encountered do not come only from the uncertainty and the possible inconsistency of information as in any information fusion situations, but also from the fact that sources may use different space partitions and may not explicitly specify the somewhere or everywhere reading associated to the information. © 2008 Elsevier B.V. All rights reserved

Update Postulates Without Inertia

. Starting from Katsuno and Mendelzon postulates, a new set of postulates which is minimal and complete has been defined, these postulates characterize an update operator. The update operator class which is obtained is larger than Katsuno and Mendelzon's one, since it includes updating operators which are not inert, and which allow for the existence of unreachable states. The main property is that every update operator satisfying this new set of postulates admits an underlying ranked transition graph. The rank-ordering of its transitions has not to be faithful as in Katsuno and Mendelzon system. 1 Introduction This paper deals with reasoning about change and especially with updating. The problem is to take into account the arrival of a new piece of information concerning a system which is represented by a knowledge base. Winslett [8] and later on Katsuno and Mendelzon [7] have shown that this piece of information can be of two kinds: either the piece of information describes the syste..

Change in Abstract Argumentation Frameworks: Adding an Argument

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DebateWEL: An interface for Debating With Enthymemes and Logical formulas ∗

The DebateWEL G.U.I. allows two players to exchange logical formulas and enthymemes in a persuasion debate game. DebateWEL protocol, described in [1], ensures consistency of each player with respect to himself and common-knowledge thanks to a SAT solver [2] which is called directly from the SAToulouse interface [3]. The game ends either because the players have found an agreement or because the limit of time has been reached (failure of the debate). Being persuasive is very useful in many situations. Indeed good orators are considered to be very clever, hence an interesting challenge for AI is to be able to design artificial persuasive orators. Before proposing such artificial agents, it is necessary to define the framework in which they are going to play. Persuasion dialogs are particular dialogs in which one agent aims at convincing others that a first assertion (called the subject of the dialog) holds. In order to design a framework in which a persuasion dialog can take place, it is necessary to define the moves that each agent is allowed to make. This definition is called a protocol. In persuasion dialogs, the possible types of moves are mainly assertions and challenges while in other kinds of dialogs (e.g. negotiations dialogs) move

Interpolation and extrapolation in conceptual spaces : A case study in the music domain

P&al038International audienceIn most knowledge representation settings, atomic properties correspond to natural language labels. Although these labels are usually taken to be primitive, automating some forms of commonsense inference requires background knowledge on the cognitive meaning of these labels. We consider two such forms of commonsense reasoning, which we refer to as interpolative and extrapolative reasoning. In both cases, rule-based knowledge is augmented with knowledge about the geometric representation of labels in a conceptual space. Specifically, to support interpolative reasoning, we need to know which labels are conceptually between which other labels, considering that intermediary conditions tend to lead to intermediary conclusions. Extrapolative reasoning is based on information about the direction of change that is needed when replacing one label by another, taking the view that parallel changes in the conditions of rules tend to lead to parallel changes in the conclusions. In this paper, we propose a practical method to acquire such knowledge about the conceptual spaces representation of labels. We illustrate the method in the domain of music genres, starting from meta-data that was obtained from the music recommendation website last.fm

The dynamics of group polarization

Exchange of arguments in a discussion often makes individuals more radical about their initial opinion. This phenomenon is known as Group-induced Attitude Polarization. A byproduct of it are bipolarization effects, where the distance between the attitudes of two groups of individuals increases after the discussion. This paper is a first attempt to analyse the building blocks of information exchange and information update that induce polarization. I use Argumentation Frameworks as a tool for encoding the information of agents in a debate relative to a given issue a. I then adapt a specific measure of the degree of acceptability of an opinion (Matt and Toni 2008). Changes in the degree of acceptability of a, prior and posterior to information exchange, serve here as an indicator of polarization. I finally show that the way agents transmit and update information has a decisive impact on polarization and bipolarization

Current Research Trends in Possibilistic Logic: Multiple Agent Reasoning, Preference Representation, and Uncertain Database

Studies in Computational Intelligence ; Series Editor : Kacprzyk, Janusz ; ISSN: 1860-949XInternational audiencePossibilistic logic is a weighted logic that handles uncertainty, or preferences, in a qualitative way by associating certainty, or priority levels, to classical logic formulas.Moreover, possibilistic logic copes with inconsistency by taking advantage of the stratification of the set of formulas induced by the associated levels. Since its introduction in the mid-eighties, multiple facets of possibilistic logic have been laid bare and various applications addressed: handling exceptions in default reasoning, modeling belief revision, providing a graphical Bayesian-like network representation counterpart to a possibilistic logic base, representing positive and negative information in a bipolar setting with applications to preferences fusion and to version space learning, extending possibilistic logic for dealing with time, or multiple agents mutual beliefs, developing a symbolic treatment of priorities for handling partial orders between levels and also improving computational efficiency, learning stratified hypotheses for coping with exceptions. The chapter aims primarily at offering an introductory survey of possibilistic logic developments. Still, it also outlines new research trends that are relevant in preference representation, or in reasoning about epistemic states