28 research outputs found

    A Complete Classification of Tractability in RCC-5

    Full text link
    We investigate the computational properties of the spatial algebra RCC-5 which is a restricted version of the RCC framework for spatial reasoning. The satisfiability problem for RCC-5 is known to be NP-complete but not much is known about its approximately four billion subclasses. We provide a complete classification of satisfiability for all these subclasses into polynomial and NP-complete respectively. In the process, we identify all maximal tractable subalgebras which are four in total.Comment: See http://www.jair.org/ for an online appendix and other files accompanying this articl

    Using a Temporal Constraint Network for Business Process Execution

    Get PDF
    Business process management (BPM) has emerged as a dominant technology in current enterprise systems and business solutions. However, the technology continues to face challenges in coping with dynamic business environments where requirements and goals are constantly changing. In this paper, we present a modelling framework for business processes that is conducive to dynamic change and the need for flexibility in execution. This framework is based on the notion of process constraints. Process constraints may be specified for any aspect of the process, such as task selection, control flow, resource allocation, etc. Our focus in this paper is on a set of scheduling constraints that are specified through a temporal constraint network. We will demonstrate how this specification can lead to increased flexibility in process execution, while maintaining a desired level of control. A key feature and strength of the approach is to use the power of constraints, while still preserving the intuition and visual appeal of graphical languages for process modelling

    PPP - personalized plan-based presenter

    Get PDF

    Concept logics

    Get PDF
    Concept languages (as used in BACK, KL-ONE, KRYPTON, LOOM) are employed as knowledge representation formalisms in Artificial Intelligence. Their main purpose is to represent the generic concepts and the taxonomical hierarchies of the domain to be modeled. This paper addresses the combination of the fast taxonomical reasoning algorithms (e.g. subsumption, the classifier etc.) that come with these languages and reasoning in first order predicate logic. The interface between these two different modes of reasoning is accomplished by a new rule of inference, called constrained resolution. Correctness, completeness as well as the decidability of the constraints (in a restricted constraint language) are shown

    A knowledge server for reasoning about temporal constraints between classes and instances of events

    Get PDF
    An outstanding example of early Reformation dress, notice the geometric fabric design, the fur-trimmed collar of the coat, and the decorative shir

    Analysing the familiar : reasoning about space and time in the everyday world

    Get PDF
    The development of suitable explicit representations of knowledge that can be manipulated by general purpose inference mechanisms has always been central to Artificial Intelligence (AI). However, there has been a distinct lack of rigorous formalisms in the literature that can be used to model domain knowledge associated with the everyday physical world. If AI is to succeed in building automata that can function reasonably well in unstructured physical domains, the development and utility of such formalisms must be secured. This thesis describes a first order axiomatic theory that can be used to encode much topological and metrical information that arises in our everyday dealings with the physical world. The formalism is notable for the minimal assumptions required in order to lift up a very general framework that can cover the representation of much intuitive spatial and temporal knowledge. The basic ontology assumes regions that can be either spatial or temporal and over which a set of relations and functions are defined. The resulting partitioning of these abstract spaces, allow complex relationships between objects and the description of processes to be formally represented. This also provides a useful foundation to control the proliferation of inference commonly associated with mechanised logics. Empirical information extracted from the domain is added and mapped to these basic structures showing how further control of inference can be secured. The representational power of the formalism and computational tractability of the general methodology proposed is substantiated using two non-trivial domain problems - modelling phagocytosis and exocytosis of uni-cellular organisms, and modelling processes arising during the cycle of operations of a force pump
    corecore