The invention of suitable concepts to characterise mathematical structures is one of the most challenging tasks for both human mathematicians and automated theorem provers alike. We present an approach where automatic concept formation is used to guide non-isomorphism proofs in the residue class domain. The main idea behind the proof is to automatically identify discriminants for two given stru...

Connict resolution in planning is the process of constraining a plan to remove harmful interactions that threaten its correctness. It has been a major contributing factor to the complexity of classical planning systems. Traditional planning methods have dealt with the problem of connict resolution in a local and incremental manner, by considering and resolving connicts individually. This paper ...

Many heuristic estimators for classical planning are based on the so-called delete relaxation, which ignores negative effects of planning operators. Ideally, such heuristics would compute the actual goal distance in the delete relaxation, i. e., the cost of an optimal relaxed plan, denoted by h. However, current delete relaxation heuristics only provide (often inadmissible) estimates to h becau...

In this paper ongoing work on an approach for planning sensing actions and controlling intelligent, purposive robotic systems is presented. The method uses Bayesian Decision Analysis (BDA) for deciding what sensing actions should be performed. This ooers a probabilistic framework that provides a more dynamic and modular behaviour than traditional rule based planners. Experiments show that the B...

In this paper we examine the general problem of generating preferred explanations for observed behavior with respect to a model of the behavior of a dynamical system. This problem arises in a diversity of applications including diagnosis of dynamical systems and activity recognition. We provide a logical characterization of the notion of an explanation. To generate explanations we identify and ...

This paper combines ideas from recent philosophical work on rational agency and work in artificial intelligence on hierarchical non-linear planners which combine plan generation, execution, and monitoring, to produce a planning theory of rational agency for resource-bounded agents.

A theory of action suitable for reasoning about events in multiagent or dynamically changing environments is prescntcrl. A device called a process model is used to represent the observable behavior of an agent in performing an action. This model is more general than previous models of act ion, allowing sequencing, selection, nondeterminism, iteration, and parallelism to be represented. It is sh...

Tiffs paper reports on recent progress addressing two issues, one of importvalce to theoretical and experimental research in generative planning and the second of importvalce to the practical application of probabilistic planning methods. The first issue concerns what makes planning problems hard from a computational perspective. We report on research investigating threshold phenomena in determ...

Decisions in supply chain (SC) planning and control are interconnected and depend on tackling SC uncertainty and dynamics. In this paper, we investigate the applicability of optimal control theory to SC planning and scheduling. The methodology of this paper is based on the literature analysis, fundamentals of control and systems theory, and our own elaborations. We describe the important issues...