546,439 research outputs found

    Logic Programming for Describing and Solving Planning Problems

    Full text link
    A logic programming paradigm which expresses solutions to problems as stable models has recently been promoted as a declarative approach to solving various combinatorial and search problems, including planning problems. In this paradigm, all program rules are considered as constraints and solutions are stable models of the rule set. This is a rather radical departure from the standard paradigm of logic programming. In this paper we revisit abductive logic programming and argue that it allows a programming style which is as declarative as programming based on stable models. However, within abductive logic programming, one has two kinds of rules. On the one hand predicate definitions (which may depend on the abducibles) which are nothing else than standard logic programs (with their non-monotonic semantics when containing with negation); on the other hand rules which constrain the models for the abducibles. In this sense abductive logic programming is a smooth extension of the standard paradigm of logic programming, not a radical departure.Comment: 8 pages, no figures, Eighth International Workshop on Nonmonotonic Reasoning, special track on Representing Actions and Plannin

    Answer Set Planning Under Action Costs

    Full text link
    Recently, planning based on answer set programming has been proposed as an approach towards realizing declarative planning systems. In this paper, we present the language Kc, which extends the declarative planning language K by action costs. Kc provides the notion of admissible and optimal plans, which are plans whose overall action costs are within a given limit resp. minimum over all plans (i.e., cheapest plans). As we demonstrate, this novel language allows for expressing some nontrivial planning tasks in a declarative way. Furthermore, it can be utilized for representing planning problems under other optimality criteria, such as computing ``shortest'' plans (with the least number of steps), and refinement combinations of cheapest and fastest plans. We study complexity aspects of the language Kc and provide a transformation to logic programs, such that planning problems are solved via answer set programming. Furthermore, we report experimental results on selected problems. Our experience is encouraging that answer set planning may be a valuable approach to expressive planning systems in which intricate planning problems can be naturally specified and solved

    Planning programming budgeting systems, selected case materials

    Get PDF
    Planning, programming, and budgeting system for operational planning by industrial managemen

    Determination of the Optimal Manpower Size Using Linear Programming Model

    Get PDF
    There would be no meaningful development lllltil manpower that involves in the transformation of production facilities into useful goods and services is well trained and planned. Recent advances in mathematical programming methodology have included:development of interior methods, competing with the simplex method, improved simplex codes, vastly improved performance for mixed-integer programming using strong linear programming formulations and a renewed interest in decomposition. Application areas have been expanding from the traditional refinery planning and distribution models to include finance, scheduling, manufacturing, manpower planning and many others. We see the acceleration of better methods and improved codes moving together with faster, lower-cost and more interesting hardware into a variety of application areas, thereby opening up new demands for greater fi.mction of optimization codes. This study applies Linear Programming (LP) model based on integer programming to the determination of effective size of manpower to be engaged. The study also incorporates global constraints such as production capacity/demand rate and allowable time of operation into the model to reflect the reality activities in production organizations in developing colUltries. The results obtained show that the model is more efficient than the existing model for effective manpower determination

    Getting Started With Market Research for Out-of-School Time Planning: A Resource Guide for Communities

    Get PDF
    Shows community leaders, policymakers, and out-of-school-time practitioners how to use market research to make more informed programming and planning decisions

    A Logic Programming Approach to Knowledge-State Planning: Semantics and Complexity

    Full text link
    We propose a new declarative planning language, called K, which is based on principles and methods of logic programming. In this language, transitions between states of knowledge can be described, rather than transitions between completely described states of the world, which makes the language well-suited for planning under incomplete knowledge. Furthermore, it enables the use of default principles in the planning process by supporting negation as failure. Nonetheless, K also supports the representation of transitions between states of the world (i.e., states of complete knowledge) as a special case, which shows that the language is very flexible. As we demonstrate on particular examples, the use of knowledge states may allow for a natural and compact problem representation. We then provide a thorough analysis of the computational complexity of K, and consider different planning problems, including standard planning and secure planning (also known as conformant planning) problems. We show that these problems have different complexities under various restrictions, ranging from NP to NEXPTIME in the propositional case. Our results form the theoretical basis for the DLV^K system, which implements the language K on top of the DLV logic programming system.Comment: 48 pages, appeared as a Technical Report at KBS of the Vienna University of Technology, see http://www.kr.tuwien.ac.at/research/reports
    corecore