We present a powerful new account of multi-agent knowledge in the situation calculus and an automated reasoning procedure for knowledge queries. Existing accounts of epistemic reasoning in the situation calculus require that whenever an action occurs, all agents know that an action has occurred. This demands a level of synchronicity that is unreasonable in many multi-agent domains. In asynchron...

In the past, little attention has been paid to critiquing in domains in which reasoning, planning and action are interleaved, or in which actions can change the agent's knowledge in ways that aaect subsequent reasoning and planning. This paper discusses the demands these characteristics make on a critiquing system. The goal-directed approach to critiquing that I am developing interacts with a p...

Access-control policies have grown from simple matrices to non-trivial specifications written in sophisticated languages. The increasing complexity of these policies demands correspondingly strong automated reasoning techniques for understanding and debugging them. The need for these techniques is even more pressing given the rich and dynamic nature of the environments in which these policies e...

Hybrid knowledge representation formalisms consist of two or more diierent subformalisms for representing diierent kinds of knowledge or knowledge in diierent kinds of representation formats. For a semantically well-founded hybrid formalism not only a precise semantics for each of the participating subformalisms has to be given but a semantics for the interrelationship between these subformalis...

In the past ten years, the areas of probabilistic inductive logic programming and statistical relational learning put forth a large collection of approaches to combine relational representations of knowledge with probabilistic reasoning. Here, we develop a series of evaluation and comparison criteria for those approaches and focus on the point of view of knowledge representation and reasoning. ...

Currently, adaptive systems are described with non-uniform methods, depending on the specific view on the system, the application, or other parameters. There is no common language for expressing adaptive functionality, hence these systems are difficult to compare and analyse, and lack of re-usability which in fact is the key-capability for successfull personalization functionality for the Seman...

Knowledge discovery in databases is a process that aims at the discovery of associations within data sets. The analysis of geo-referenced data demands a particular approach in this process. This chapter presents a new approach to the process of knowledge discovery, in which qualitative geographic identifiers give the positional aspects of geographic data. Those identifiers are manipulated using...

Research in (medical) terminological knowledge representation is showing an increased interest in the family of Description Logics (DLs), as they allow for automatic reasoning. This interest is driven by an increase in demands on the quality of and reasoning ability with medical terminological knowledge. Recent advances in Computer Science have demonstrated the computational decidability and em...

Formal nonmonotonic reasoning provides a promising basis for meeting the demands inherent in the incomplete, evolving and inconsistent requirements that characterise large-scale industrial software systems. This paper explores formal reasoning in requirements analysis, design and implementation. It indicates how the notion of provability in maximal consistency logics might be used to extend cur...

As we move towards a richer model of computation based on interactions among autonomous agents in lieu of the more traditional numeric batch processing model, it is necessary to devise techniques and abstractions for the development of such autonomous agents. The ability to generate, reason about, and select the means to achieve explicit goals is critical for autonomous agents, the so called go...