In this paper we give a short introduction to logic programming approach to knowledge representation and reasoning. The intention is to help the reader to develop a 'feel' for the field's history and some of its recent developments. The discussion is mainly limited to logic programs under the answer set semantics. For understanding of approaches to logic programming build on well-founded semantics, general theories of argumentation, abductive reasoning, etc., the reader is referred to other publications.

Logic programming has often been considered less than adequate for modelling the dynamics of knowledge changing over time.

We show how to compile programs formalizing update plus preference reasoning into standard generalized logic programs and show the correctness of the transformation.

Recently, several approaches for updating knowledge bases represented as logic programs have been proposed. In this paper, we present a generic framework for declarative specifications of update policies, which is built upon such approaches. It extends the LUPS language for update specifications and incorporates the notion of events into the framework. An update policy allows an agent to flexibly react upon new information, arriving as an event, and perform suitable changes of its knowledge base. The framework compiles update policies to logic programs by means of generic translations, and can be instantiated in terms of different concrete update approaches. It thus provides a flexible tool for designing adaptive reasoning agents. 1

The agent paradigm, commonly implemented by means of imperative languages mainly for reasons of efficiency, has recently increased its influence in the research and development of computational logic based systems. Since efficiency is not always the crucial issue, but clear specification and correctness is, Logic Programming and Non-monotonic Reasoning have been brought back into the spotlight. To this accrues the recent significant improvements in the efficiency of Logic Programming implementations for Non-monotonic Reasoning.

According to Dynamic Logic Programming (DLP), knowledge may be given by a set of theories (encoded as logic programs) representing different states of knowledge. These may represent time (in updates), specificity (in taxonomies), strength of updating instance (in the legislative domain), hierarchical position of knowledge source (in organizations), etc. The mutual relationships extant among states are used to determine the semantics of the combined theory composed of all the individual theories. Although suitable to encode a single dimension (e.g. time, hierarchies...), DLP cannot deal with more than one simultaneously because it is defined only for a linear sequence of states. To overcome this limitation, we introduce the notion of Multi-dimensional Dynamic Logic Programming (MDLP), which generalizes DLP to collections of states organized in arbitrary acyclic digraphs representing precedence. In this setting, MDLP assigns semantics to sets and subsets of such logic ...

. This paper reports on the use of logic program updates to models actions that bring about changes in knowledge states describing the world and its rules. The LUPS language is employed to specify concurrent update rules to model actions that depend on, and change, rule rich world states, not described simply by propositional fluents. This language and corresponding semantics, whose original stable semantics we generalize to the well-founded setting, is briefly recapitulated here. The advantages of our approach to modelling actions as updates are brought out by a number of telling examples, especially conceived for the purpose. They have been test run in our implementation of LUPS, though the latter is not described here for lack of space. Keywords: Updates, actions, LP semantics. 1 Introduction Traditionally, Logic Programming (LP) has allowed us to declaratively specify and query the semantics of non-monotonic Knowledge Base (KB) states. Of late, LP has been pressed into...

The concept of an agent is increasingly used in contemporary software applications, particularly those involving the Internet, autonomous systems, or cooperation. However, with dependability and safety in mind, it is vital that the mechanisms for representing and implementing agents are clear and consistent. Hence there has been a strong research effort directed at using formal logic as the basis for agent descriptions and agent implementation. Such a logical basis not only presents the clarity and consistency required but also allows for important techniques such as logical verification to be applied. We present a roadmap of research into the use of computational logic in agent-based systems and survey much of the recent work in these areas. Even though, with such a rapidly changing field, it is impossible to cover every development, we aim to give the reader sufficient background to understand the current research problems and potential future developments in this maturing area.

a computational logic model for the description, analysis and verification of global and open societies of heterogeneous computees IST-2001-32530 Deliverable D4: A logic-based approach to model computees Project number:

This paper explores the applicability of the new paradigm of Multi-dimensional Dynamic Logic Programming to represent an agent’s view of the combination of societal knowledge dynamics. The representation of a dynamic society of agents is the core of MIN ERVA [11], an agent architecture and system designed with the intention of providing a common agent framework based on the unique strengths of Logic Programming, hat allows the combination of several non-monotonic knowledge representation and reasoning mechanisms developed in recent years.