A Compact Argumentation System for Agent System Specification

We present a non-monotonic logic tailored for specifying compact autonomous agent systems. The language is a consistent instantiation of a logic based argumentation system extended with Brooks' subsumption concept and varying degree of belief. Particularly, we present a practical implementation of the language by developing a meta-encoding method that translates logical specifications into compact general logic programs. The language allows n-ary predicate literals with the usual first-order term definitions. We show that the space complexity of the resulting general logic program is linear to the size of the original theory

Proposal of fuzzy object oriented model in extended JAVA

The knowledge imperfections should be considered when modeling complex problems. A solution is to develop a model that reduces the complexity and another option is to represent the imperfections: uncertainty, vagueness and incompleteness in the knowledge base. This paper proposes to extend the classical object oriented architecture in order to allow modeling of problems with intrinsic imperfections. The aim is to use the JAVA object oriented architecture to carry out this objective. In consequence, it is necessary to define the semantics for this extension of JAVA and it will be called Fuzzy JAVA. The NCR FuzzyJ library allows represent the vagueness (fuzziness) and uncertainty in class attributes. JAVA extended allows to model fuzzy inheritance.Applications in Artificial Intelligence - Knowledge EngineeringRed de Universidades con Carreras en Informática (RedUNCI

A simple logic for reasoning about incomplete knowledge

International audienceThe semantics of modal logics for reasoning about belief or knowledge is often described in terms of accessibility relations, which is too expressive to account for mere epistemic states of an agent. This paper proposes a simple logic whose atoms express epistemic attitudes about formulae expressed in another basic propositional language, and that allows for conjunctions, disjunctions and negations of belief or knowledge statements. It allows an agent to reason about what is known about the beliefs held by another agent. This simple epistemic logic borrows its syntax and axioms from the modal logic KD. It uses only a fragment of the S5 language, which makes it a two-tiered propositional logic rather than as an extension thereof. Its semantics is given in terms of epistemic states understood as subsets of mutually exclusive propositional interpretations. Our approach offers a logical grounding to uncertainty theories like possibility theory and belief functions. In fact, we define the most basic logic for possibility theory as shown by a completeness proof that does not rely on accessibility relations

Proposal of fuzzy object oriented model in extended JAVA

The knowledge imperfections should be considered when modeling complex problems. A solution is to develop a model that reduces the complexity and another option is to represent the imperfections: uncertainty, vagueness and incompleteness in the knowledge base. This paper proposes to extend the classical object oriented architecture in order to allow modeling of problems with intrinsic imperfections. The aim is to use the JAVA object oriented architecture to carry out this objective. In consequence, it is necessary to define the semantics for this extension of JAVA and it will be called Fuzzy JAVA. The NCR FuzzyJ library allows represent the vagueness (fuzziness) and uncertainty in class attributes. JAVA extended allows to model fuzzy inheritance.Applications in Artificial Intelligence - Knowledge EngineeringRed de Universidades con Carreras en Informática (RedUNCI

Multi-dimensional knowledge representation with a fuzzy extension

Abstract This paper presents some prefiminary results of our current attempts to develop a hybrid multi-dimensional knowledge representation scheme which can handle both the incompleteness and uncertainty. We have started from the quantitative temporal constraint information, and extended it with possibilistic quantifiers. We have also extended the former towards a multidimensional constraint-based formalism. Finally we have combined these two extensions under a multi-dimensional possibilistic scheme. The context of spatio-temporal reasoning is one of the motivations for developing such a hybrid scheme. However, the major motivation for our work is coming from the muti-dimensional data modeling research[SHJM96] within the database area