Cognitive Defeasible Reasoning: the Extent to Which Forms of Defeasible Reasoning Correspond with Human Reasoning

Classical logic forms the basis of knowledge representation and reasoning in AI. In the real world, however, classical logic alone is insufficient to describe the reasoning behaviour of human beings. It lacks the flexibility so characteristically required of reasoning under uncer- tainty, reasoning under incomplete information and reasoning with new information, as humans must. In response, non-classical extensions to propositional logic have been formulated, to provide non-monotonicity. It has been shown in previous studies that human reasoning exhibits non- monotonicity. This work is the product of merging three independent studies, each one focusing on a different formalism for non-monotonic reasoning: KLM defeasible reasoning, AGM belief revision and KM belief update. We investigate, for each of the postulates propounded to characterise these logic forms, the extent to which they have correspondence with human reasoners. We do this via three respective experiments and present each of the postulates in concrete and abstract form. We discuss related work, our experiment design, testing and evaluation, and report on the results from our experiments. We find evidence to believe that 1 out of 5 KLM defeasible reasoning postulates, 3 out of 8 AGM belief revi- sion postulates and 4 out of 8 KM belief update postulates conform in both the concrete and abstract case. For each experiment, we performed an additional investigation. In the experiments of KLM defeasible rea- soning and AGM belief revision, we analyse the explanations given by participants to determine whether the postulates have a normative or descriptive relationship with human reasoning. We find evidence that suggests, overall, KLM defeasible reasoning has a normative relationship with human reasoning while AGM belief revision has a descriptive rela- tionship with human reasoning. In the experiment of KM belief update, we discuss counter-examples to the KM postulates

Reason Maintenance - State of the Art

This paper describes state of the art in reason maintenance with a focus on its future usage in the KiWi project. To give a bigger picture of the field, it also mentions closely related issues such as non-monotonic logic and paraconsistency. The paper is organized as follows: first, two motivating scenarios referring to semantic wikis are presented which are then used to introduce the different reason maintenance techniques

Belief Revision in Structured Probabilistic Argumentation

In real-world applications, knowledge bases consisting of all the information at hand for a specific domain, along with the current state of affairs, are bound to contain contradictory data coming from different sources, as well as data with varying degrees of uncertainty attached. Likewise, an important aspect of the effort associated with maintaining knowledge bases is deciding what information is no longer useful; pieces of information (such as intelligence reports) may be outdated, may come from sources that have recently been discovered to be of low quality, or abundant evidence may be available that contradicts them. In this paper, we propose a probabilistic structured argumentation framework that arises from the extension of Presumptive Defeasible Logic Programming (PreDeLP) with probabilistic models, and argue that this formalism is capable of addressing the basic issues of handling contradictory and uncertain data. Then, to address the last issue, we focus on the study of non-prioritized belief revision operations over probabilistic PreDeLP programs. We propose a set of rationality postulates -- based on well-known ones developed for classical knowledge bases -- that characterize how such operations should behave, and study a class of operators along with theoretical relationships with the proposed postulates, including a representation theorem stating the equivalence between this class and the class of operators characterized by the postulates

Embedding defeasible argumentation in the semantic web: an ontology-based approach

The SemanticWeb is a project intended to create a universal medium for information exchange by giving semantics to the content of documents on the Web by means of ontology definitions. Ontologies intended for knowledge representation in intelligent agents rely on common-sense reasoning formalizations. Defeasible argumentation has emerged as a successful approach to model common-sense reasoning. Recent research has linked argumentation with belief revision in order to model the dynamics of knowledge. This paper outlines an approach which combines ontologies, argumentation and belief revision by defining an ontology algebra. We suggest how different aspects of ontology integration can be defined in terms of defeasible argumentation and belief revision.Eje: Inteligencia artificialRed de Universidades con Carreras en Informática (RedUNCI

Some approaches to Belief Bases Merge

In this work, we de fine some non-prioritized merge operators, that is, operators for the consistent union of belief bases. We de ne some postulates for several kinds of merge operator and we give different constructions: trivial merge, partial meet merge and kernel merge. For some constructions we provide representation theorems linking construction with a set of postulates. Finally, we propose that the formulated operators can be used in some multi-agent systemsVII Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

A preliminary investigation on a revision-based approach to the status of warrant

In this article we are presenting a new perspective on the matter of belief revision by its relation to argumentation systems. Our approach is based on the argumentative formalism Defeasible Logic Programming, and therefore we propose a revision of a defeasible logic program by an argument. The revision operators here introduced are de ned as prioritized, since they ensure warrant of the conclusion of the argument being added to the program following a particular minimal change principle. To achieve this, we give two different approaches: one regarding arguments in the classical sense, whereas the other considers the revision by arguments that also include strict rules and facts. Finally, a brief discussion about the relation between our approach and the basic theory of belief revision is exposed, along with a description of other possible minimal change principles.Red de Universidades con Carreras en Informática (RedUNCI