4,500 research outputs found

    Research in advanced formal theorem-proving techniques

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    The results are summarised of a project aimed at the design and implementation of computer languages to aid in expressing problem solving procedures in several areas of artificial intelligence including automatic programming, theorem proving, and robot planning. The principal results of the project were the design and implementation of two complete systems, QA4 and QLISP, and their preliminary experimental use. The various applications of both QA4 and QLISP are given

    Proceedings of the 2nd Computer Science Student Workshop: Microsoft Istanbul, Turkey, April 9, 2011

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    Reinforcement planning for resource allocation and constraint satisfaction

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    Informed selection and use of training examples for knowledge refinement.

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    Knowledge refinement tools seek to correct faulty rule-based systems by identifying and repairing faults indicated by training examples that provide evidence of faults. This thesis proposes mechanisms that improve the effectiveness and efficiency of refinement tools by the best use and selection of training examples. The refinement task is sufficiently complex that the space of possible refinements demands a heuristic search. Refinement tools typically use hill-climbing search to identify suitable repairs but run the risk of getting caught in local optima. A novel contribution of this thesis is solving the local optima problem by converting the hill-climbing search into a best-first search that can backtrack to previous refinement states. The thesis explores how different backtracking heuristics and training example ordering heuristics affect refinement effectiveness and efficiency. Refinement tools rely on a representative set of training examples to identify faults and influence repair choices. In real environments it is often difficult to obtain a large set of training examples, since each problem-solving task must be labelled with the expert's solution. Another novel aspect introduced in this thesis is informed selection of examples for knowledge refinement, where suitable examples are selected from a set of unlabelled examples, so that only the subset requires to be labelled. Conversely, if a large set of labelled examples is available, it still makes sense to have mechanisms that can select a representative set of examples beneficial for the refinement task, thereby avoiding unnecessary example processing costs. Finally, an experimental evaluation of example utilisation and selection strategies on two artificial domains and one real application are presented. Informed backtracking is able to effectively deal with local optima by moving search to more promising areas, while informed ordering of training examples reduces search effort by ensuring that more pressing faults are dealt with early on in the search. Additionally, example selection methods achieve similar refinement accuracy with significantly fewer examples

    Revisiting the "Compliance-vs.-Rebalancing" Debate in WTO Scholarship a Unified Research Agenda

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    This paper constitutes an attempt to reframe and eventually deflate the ongoing “compliance-vs.-rebalancing” debate which has permeated WTO scholarship for the last 10 years. At face value, this controversy circles around object and purpose of WTO enforcement and the legal nature of dispute panels’ recommendations: Compliance advocates maintain that the objective of WTO enforcement is to induce compliance with DSB panel/AB rulings, and to deter future violations of the Agreement, while rebalancing advocates detect an inherent “pay-or-perform” logic in WTO enforcement. In the paper we examine the shortcomings of each approach separately. Our main criticism, however, concerns the substance of the entire debate. We find that scholars on both sides of the compliance/rebalancing controversy put an unduly rigid emphasis on the subsequent issues of WTO enforcement and the interpretation of the wording of the dispute settlement understanding. They thereby neglected systemic issues of contracting, viz. the nature of contractual entitlements, the need for trade policy flexibility mechanisms and the optimal design of the appropriate remedies. We redefine and recalibrate the compliance/rebalancing controversy along the lines of the nature of the WTO contract. This results in to three key findings: First, none of the two schools of thought succeeds in giving an accurate picture of the WTO treaty. Second, the two perspectives actually portray two strikingly different concepts of the WTO contract, and therefore have been at cross-purposes from the very beginning. This implies a third finding: The two schools of thought essentially describe different facets of the same complex WTO contract. Hence, they have hardly been at loggerheads at all, and are actually complementing each other in important aspects. We lay out a unified research agenda that practitioners, economists, trade lawyers, and international relations scholars alike can accept. The agenda may contribute to reconciling the two opposing views and help WTO scholarship tackle the real systemic issues of the WTO Agreement.WTO, dispute settlement, incomplete contracts, remedies, enforcement

    Resource-constrained project scheduling.

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    Abstract: Resource-constrained project scheduling involves the scheduling of project activities subject to precedence and resource constraints in order to meet the objective(s) in the best possible way. The area covers a wide variety of problem types. The objective of this paper is to provide a survey of what we believe are important recent in the area . Our main focus will be on the recent progress made in and the encouraging computational experience gained with the use of optimal solution procedures for the basic resource-constrained project scheduling problem (RCPSP) and important extensions. The RCPSP involves the scheduling of a project its duration subject to zero-lag finish-start precedence constraints of the PERT/CPM type and constant availability constraints on the required set of renewable resources. We discuss recent striking advances in dealing with this problem using a new depth-first branch-and-bound procedure, elaborating on the effective and efficient branching scheme, bounding calculations and dominance rules, and discuss the potential of using truncated branch-and-bound. We derive a set of conclusions from the research on optimal solution procedures for the basis RCPSP and subsequently illustrate how effective and efficient branching rules and several of the strong dominance and bounding arguments can be extended to a rich and realistic variety of related problems. The preemptive resource-constrained project scheduling problem (PRCPSP) relaxes the nonpreemption condition of the RCPSP, thus allowing activities to be interrupted at integer points in time and resumed later without additional penalty cost. The generalized resource-constrained project scheduling (GRCPSP) extends the RCPSP to the case of precedence diagramming type of precedence constraints (minimal finish-start, start-start, start-finish, finish-finish precedence relations), activity ready times, deadlines and variable resource availability's. The resource-constrained project scheduling problem with generalized precedence relations (RCPSP-GPR) allows for start-start, finish-start and finish-finish constraints with minimal and maximal time lags. The MAX-NPV problem aims at scheduling project activities in order to maximize the net present value of the project in the absence of resource constraints. The resource-constrained project scheduling problem with discounted cash flows (RCPSP-DC) aims at the same non-regular objective in the presence of resource constraints. The resource availability cost problem (RACP) aims at determining the cheapest resource availability amounts for which a feasible solution exists that does not violate the project deadline. In the discrete time/cost trade-off problem (DTCTP) the duration of an activity is a discrete, non-increasing function of the amount of a single nonrenewable resource committed to it. In the discrete time/resource trade-off problem (DTRTP) the duration of an activity is a discrete, non-increasing function of the amount of a single renewable resource. Each activity must then be scheduled in one of its possible execution modes. In addition to time/resource trade-offs, the multi-mode project scheduling problem (MRCPSP) allows for resource/resource trade-offs and constraints on renewable, nonrenewable and doubly-constrained resources. We report on recent computational results and end with overall conclusions and suggestions for future research.Scheduling; Optimal;
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