Pruning multi-extensions via exceptions

The main contribution of this paper is a method for pruning multi-extensions of a defeasible theory by using the exceptions to order the defeasible fonnulae. We construct a defeasible logic -- DEFEASIBLE WGIC WrrH EXCEFrIONS FIRST(DLEF) -- in which extensions are buílt taking into account the order on the defeasible fonnu1ae induced by the exceptions. This device prompts DLEF as a powerful tool to formalize common sense reasoning. It is on the formalization of the frame problem that we best evaluate the original features of DLEF. DLEF allows the formalization of the persistence axiom in the temporal projection problem in a stepwise way. That is, the persistence axiom is applied locally after every action is performed. Thus, if no exception to sorne properties is present while an action is performed the persistence axiom is used to conclude that those properties will remain unaltered in the resulting situation. Therefore, no property at the present is changed just for the sake of not changing sorne other properties in the future. The only reason for changes in properties are explicit changes provoked by the action being perfonned at the moment.Eje: 2do. Workshop sobre aspectos teóricos de la inteligencia artificialRed de Universidades con Carreras en Informática (RedUNCI

About the use of time on argumentative systems

There are many areas in Computer Science where time plays an important role. Artificial Intelligence is one of them. In this particular area Defeasible Logic Programming (DeLP) was developed to cope with incomplete and potentially inconsistent information. This formalism combines results from Logic Programming and Defeasible Argumentation. DeLP in particular provides the possibility of representing defeasible information in a declarative way and a defeasible argumentation inference mechanism to warrant conclusions. Although this formalism and Defeasible logic programming in general are very useful has left apart an issue that is crucial on several kind of problems, namely time. There are also many developments that face temporal reasoning, in particular Event Calculus, but non of them consider defeasible information or what to do if we have incomplete or not completely reliable information. In this work we try to attempt an exploration of a possible combination of these two reasoning areas, temporal and defeasible.Eje: VI Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

Explaining Actual Causation via Reasoning About Actions and Change

In causality, an actual cause is often defined as an event responsible for bringing about a given outcome in a scenario. In practice, however, identifying this event alone is not always sufficient to provide a satisfactory explanation of how the outcome came to be. In this paper, we motivate this claim using well-known examples and present a novel framework for reasoning more deeply about actual causation. The framework reasons over a scenario and domain knowledge to identify additional events that helped to "set the stage" for the outcome. By leveraging techniques from Reasoning about Actions and Change, the approach supports reasoning over domains in which the evolution of the state of the world over time plays a critical role and enables one to identify and explain the circumstances that led to an outcome of interest. We utilize action language AL for defining the constructs of the framework. This language lends itself quite naturally to an automated translation to Answer Set Programming, using which, reasoning tasks of considerable complexity can be specified and executed. We speculate that a similar approach can also lead to the development of algorithms for our framework

Towards a comparison criteria for CDeLP

The development of systems with the ability to reason about change notion and actions has been of great importance for the artificial intelligence community. The definition and implementation of systems capable of managing defeasible, incomplete, unreliable, or uncertain information has been also an area of much interest. With a few exceptions research on these two ways of reasoning was independently pursued. Nevertheless, they are complementary and closely related, since many applications that deal with defeasible information also depends on the occurrence of events and time. DeLP is an argumentative system appropriate for commonsense reasoning. The defeasible argumentation basis of DeLP allows to build applications that deal with incomplete and contradictory information in dynamic domains. Thus, the resulting approach is suitable for representing agent’s knowledge and for providing an argumentation based reasoning mechanism for that agent (see for example [6, 1]). It is interesting to extend this system adding mechanisms to manage events and time as CDeLP [7]. Here we analyze how to develop a comparison criteria for arguments built up from causal information and considers commonsense rules of inertia.VIII Workshop de Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

Disjunctive Logic Programs with Inheritance

The paper proposes a new knowledge representation language, called DLP<, which extends disjunctive logic programming (with strong negation) by inheritance. The addition of inheritance enhances the knowledge modeling features of the language providing a natural representation of default reasoning with exceptions. A declarative model-theoretic semantics of DLP< is provided, which is shown to generalize the Answer Set Semantics of disjunctive logic programs. The knowledge modeling features of the language are illustrated by encoding classical nonmonotonic problems in DLP<. The complexity of DLP< is analyzed, proving that inheritance does not cause any computational overhead, as reasoning in DLP< has exactly the same complexity as reasoning in disjunctive logic programming. This is confirmed by the existence of an efficient translation from DLP< to plain disjunctive logic programming. Using this translation, an advanced KR system supporting the DLP< language has been implemented on top of the DLV system and has subsequently been integrated into DLV.Comment: 28 pages; will be published in Theory and Practice of Logic Programmin

Pruning multi-extensions via exceptions

The main contribution of this paper is a method for pruning multi-extensions of a defeasible theory by using the exceptions to order the defeasible fonnulae. We construct a defeasible logic -- DEFEASIBLE WGIC WrrH EXCEFrIONS FIRST(DLEF) -- in which extensions are buílt taking into account the order on the defeasible fonnu1ae induced by the exceptions. This device prompts DLEF as a powerful tool to formalize common sense reasoning. It is on the formalization of the frame problem that we best evaluate the original features of DLEF. DLEF allows the formalization of the persistence axiom in the temporal projection problem in a stepwise way. That is, the persistence axiom is applied locally after every action is performed. Thus, if no exception to sorne properties is present while an action is performed the persistence axiom is used to conclude that those properties will remain unaltered in the resulting situation. Therefore, no property at the present is changed just for the sake of not changing sorne other properties in the future. The only reason for changes in properties are explicit changes provoked by the action being perfonned at the moment.Eje: 2do. Workshop sobre aspectos teóricos de la inteligencia artificialRed de Universidades con Carreras en Informática (RedUNCI

Modelling default and likelihood reasoning as probabilistic

A probabilistic analysis of plausible reasoning about defaults and about likelihood is presented. 'Likely' and 'by default' are in fact treated as duals in the same sense as 'possibility' and 'necessity'. To model these four forms probabilistically, a logic QDP and its quantitative counterpart DP are derived that allow qualitative and corresponding quantitative reasoning. Consistency and consequence results for subsets of the logics are given that require at most a quadratic number of satisfiability tests in the underlying propositional logic. The quantitative logic shows how to track the propagation error inherent in these reasoning forms. The methodology and sound framework of the system highlights their approximate nature, the dualities, and the need for complementary reasoning about relevance