The role of attention in robot self-awareness

A robot may not be truly self-aware even though it can have some characteristics of self-awareness, such as having emotional states or the ability to recognize itself in the mirror. We define self-awareness in robots to be characterized by the capacity to direct attention toward their own mental state. This paper explores robot self-awareness and the role that attention plays in the achievement self-awareness. We propose a new attention based approach to self-awareness called ASMO and conduct a comparative analysis of approaches that highlights the innovation and benefits of ASMO. We then describe how our attention based self-awareness can be designed and used to develop self-awareness in state-of-the-art humanoidal robots. © 2009 IEEE

Belief Revision, Minimal Change and Relaxation: A General Framework based on Satisfaction Systems, and Applications to Description Logics

Belief revision of knowledge bases represented by a set of sentences in a given logic has been extensively studied but for specific logics, mainly propositional, and also recently Horn and description logics. Here, we propose to generalize this operation from a model-theoretic point of view, by defining revision in an abstract model theory known under the name of satisfaction systems. In this framework, we generalize to any satisfaction systems the characterization of the well known AGM postulates given by Katsuno and Mendelzon for propositional logic in terms of minimal change among interpretations. Moreover, we study how to define revision, satisfying the AGM postulates, from relaxation notions that have been first introduced in description logics to define dissimilarity measures between concepts, and the consequence of which is to relax the set of models of the old belief until it becomes consistent with the new pieces of knowledge. We show how the proposed general framework can be instantiated in different logics such as propositional, first-order, description and Horn logics. In particular for description logics, we introduce several concrete relaxation operators tailored for the description logic \ALC{} and its fragments \EL{} and \ELext{}, discuss their properties and provide some illustrative examples

Prioritized base debugging in Description Logics

Abstract The problem investigated is the identification within an input knowledge base of axioms which should be preferably discarded (or amended) in order to restore consistency, coherence, or get rid of undesired consequences. Most existing strategies for this task in Description Logics rely on conflicts, either computing all minimal conflicts beforehand, or generating conflicts on demand, using diagnosis. The article studies how prioritized base revision can be effectively applied in the former case. The first main contribution is the observation that for each axiom appearing in a minimal conflict, two bases can be obtained for a negligible cost, representing what part of the input knowledge must be preserved if this axiom is discarded or retained respectively, and which may serve as a basis to obtain a semantically motivated preference relation over these axioms. The second main contributions is an algorithm which, assuming this preference relation is known, selects some of the maximal consistent/coherent subsets of the input knowledge base accordingly, without the need to compute all of of them

Typicality-based revision for handling exceptions in Description Logics

Abstract. We continue our investigation on how to revise a Description Logic knowledge base when detecting exceptions. Our approach relies on the methodology for debugging a Description Logic terminology, addressing the problem of diagnosing inconsistent ontologies by identifying a minimal subset of axioms responsible for an inconsistency. In the approach we propose, once the source of the inconsistency has been localized, the identified TBox inclusions are revised in order to obtain a consistent knowledge base including the detected exception. We define a revision operator whose aim is to replace inclusions of the form "Cs are Ds" with "typical Cs are Ds", admitting the existence of exceptions, obtaining a knowledge base in the nonmonotonic logic ALC R min T which corresponds to a notion of rational closure for Description Logics of typicality. We also describe an algorithm implementing such a revision operator

Weakening conflicting information for iterated revision and knowledge integration

The ability to handle exceptions, to perform iterated belief revision and to integrate information from multiple sources is essential for a commonsense reasoning agent. These important skills are related in the sense that they all rely on resolving inconsistent information. In this paper we develop a novel and useful strategy for conflict resolution, and compare and contrast it with existing strategies. Ideally the process of conflict resolution should conform with the principle of Minimal Change and should result in the minimal loss of information. Our approach to minimizing the loss of information is to weaken information involved in conflicts rather than completely discarding it. We implemented and tested the relative performance of our new strategy in three different ways. Surprisingly, we are able to demonstrate that it provides a computationally effective compilation of the lexicographical strategy; a strategy which is known to have desirable theoretical properties. © 2003 Elsevier B.V. All rights reserved