We investigate the role of symmetry detection and symmetry breaking in answer set programming to eliminate symmetric parts of the search space and, thereby, simplify the solution process. We reduce symmetry detection ...
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We investigate the role of symmetry detection and symmetry breaking in answer set programming to eliminate symmetric parts of the search space and, thereby, simplify the solution process. We reduce symmetry detection to a graph automorphism problem which allows us to extract symmetries of a logic program from the symmetries of the constructed coloured graph. The correctness of our reduction is proven. We also propose an encoding of symmetry-breaking constraints in terms of permutation cycles and use only generators in this process to implicitly represent symmetries with exponential compression. These ideas are formulated as preprocessing and implemented in a completely automated flow that first detects symmetries from a given answerset program, adds symmetry-breaking constraints, and can be applied to any existing answerset solver. We demonstrate computational impact on benchmarks versus direct application of the solver.
This paper gives an overview of the open source project Potassco, the Potsdam answerset Solving Collection, bundling tools for answer set programming developed at the University of Potsdam.
This paper gives an overview of the open source project Potassco, the Potsdam answerset Solving Collection, bundling tools for answer set programming developed at the University of Potsdam.
Indoor position estimation constitutes a central task in home-based assisted living environments. Such environments often rely on a heterogeneous collection of low-cost sensors whose diversity and lack of precision ha...
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Indoor position estimation constitutes a central task in home-based assisted living environments. Such environments often rely on a heterogeneous collection of low-cost sensors whose diversity and lack of precision has to be compensated by advanced techniques for localization and tracking. Although there are well established quantitative methods in robotics and neighboring fields for addressing these problems, they lack advanced knowledge representation and reasoning capacities. Such capabilities are not only useful in dealing with heterogeneous and incomplete information but moreover they allow for a better inclusion of semantic information and more general homecare and patient-related knowledge. We address this problem and investigate how state-of-the-art localization and tracking methods can be combined with answer set programming, as a popular knowledge representation and reasoning formalism. We report upon a case-study and provide a first experimental evaluation of knowledge-based position estimation both in a simulated as well as in a real setting.
This paper presents the Argonauts multi-agent framework which was developed as part of a one year student project at Technische Universitat Dortmund. The Argonauts framework builds on a BDI approach to model rational ...
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This paper presents the Argonauts multi-agent framework which was developed as part of a one year student project at Technische Universitat Dortmund. The Argonauts framework builds on a BDI approach to model rational agents that act cooperatively in a dynamic and indeterministically changing environment. However, our agent model extends the traditional BDI approach in several aspects, most notably by incorporating motivation into the agent's goal selection mechanism. The framework has been applied by the Argonauts team in the 2010 version of the annual multi-agent programming contest organized by Technische Universitat Clausthal. In this paper, we present a high-level specification and analysis of the actual system used for solving the given scenario. We do this by applying the GAIA methodology, a high-level and iterative approach to model communication and roles in multi-agent scenarios. We further describe the technical details and insights gained during our participation in the multi-agent programming contest.
We present the General Game Playing system Centurio. Centurio is a Java-based player featuring different strategies based on Monte Carlo Tree Search extended by techniques borrowed from Upper Confidence bounds applied...
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We present the General Game Playing system Centurio. Centurio is a Java-based player featuring different strategies based on Monte Carlo Tree Search extended by techniques borrowed from Upper Confidence bounds applied to Trees as well as answer set programming (for single-player games). Centurio's Monte Carlo Tree Search is accomplished in a massively parallel way by means of multi-threading as well as cluster-computing. Another major feature of Centurio is its compilation of game descriptions, states, and state manipulations into Java, yielding an edge over existing Prolog-based approaches. Centurio is open source software freely available via the web.
For some problems with too many solutions, one way to obtain the more desirable solutions is to assign each solution a weight that characterizes its importance quantitatively, and then compute the solutions whose weig...
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For some problems with too many solutions, one way to obtain the more desirable solutions is to assign each solution a weight that characterizes its importance quantitatively, and then compute the solutions whose weights are over (resp. below) a given threshold. This paper studies computing weighted solutions for a given computational problem, in the context of answer set programming (ASP). In particular, we investigate two sorts of methods for computing weighted solutions: one method suggests modifying the ASP representation of the problem to compute weighted solutions using an existing ASP solver and the other suggests modifying the search algorithm of the answerset solver to compute weighted solutions incrementally. The applicability of these methods are shown on two sorts of problems: reconstructing weighted phylogenies (for Indo-European languages and for Quercus species) and finding weighted plans (for Blocks World planning problems). In the experiments with the representation-based method, the answerset solver clasp is used and weight functions are represented in ASP. For the search-based method, the algorithm of clasp is modified (the modified solver is called CLASP-W) and weight functions are implemented in C++. For phylogenies, two weight functions are introduced by incorporating domain-specific information about groupings of species;one of them cannot be represented in ASP due to some mathematical functions not supported by the ASP solvers. For plans, we define a weight function that characterizes the total cost of executing actions in a plan. In these experiments the following are observed. With weight measures that can be represented in ASP, the search-based method outperforms the representation-based method in terms of computational efficiency (both time and space). With weight functions that cannot be represented in ASP, the search-based method provides a tool for computing weighted solutions in ASP. The search-based method can be applied to differe
Nieuwenhuis et al. (2006. Solving SAT and SAT modulo theories: From an abstract Davis-Putnam-Logemann-Loveland procedure to DPLL(T). Journal of the ACM 53(6), 937977 showed how to describe enhancements of the Davis-Pu...
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Nieuwenhuis et al. (2006. Solving SAT and SAT modulo theories: From an abstract Davis-Putnam-Logemann-Loveland procedure to DPLL(T). Journal of the ACM 53(6), 937977 showed how to describe enhancements of the Davis-Putnam-Logemann-Loveland algorithm using transition systems, instead of pseudocode. We design a similar framework for several algorithms that generate answersets for logic programs: SMODELS, SMODELScc, asp-sat with Learning (CMODELS), and a newly designed and implemented algorithm sup. This approach to describe answerset solvers makes it easier to prove their correctness, to compare them, and to design new systems.
Image processing is becoming more and more present in our everyday life. With the requirements of miniaturization, low-power, performance in order to provide some intelligent processing directly into the camera, embed...
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ISBN:
(纸本)9781457706608
Image processing is becoming more and more present in our everyday life. With the requirements of miniaturization, low-power, performance in order to provide some intelligent processing directly into the camera, embedded camera will dominate the image processing landscape in the future. While the common approach of developing such embedded systems is to use sequentially operating processors, image processing algorithms are inherently parallel, thus hardware devices like FPGAs provide a perfect match to develop highly efficient systems. Unfortunately hardware development is more difficult and there are less experts available compared to software. Automatizing the design process will leverage the existing infrastructure, thus providing faster time to market and quick investigation of new algorithms. We exploit ASP (answer set programming) for system synthesis with the goal of genarating an optimal hardware software partitioning, a viable communication structure and the corresponding scheduling, from an image processing application.
In recent years there has been a growing interest in solutions for the delivery of clinical care for the elderly because of the large increase in aging population. Monitoring a patient in his home environment is neces...
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In recent years there has been a growing interest in solutions for the delivery of clinical care for the elderly because of the large increase in aging population. Monitoring a patient in his home environment is necessary to ensure continuity of care in home settings, but, to be useful, this activity must not be too invasive for patients and a burden for caregivers. We prototyped a system called Secure and IN Dependent lIving (SINDI), focused on (a) collecting a limited amount of data about the person and the environment through Wireless Sensor Networks (WSN), and (b) inferring from these data enough information to support caregivers in understanding patients' well-being and in predicting possible evolutions of their health. Our hierarchical logic-based model of health combines data from different sources, sensor data, tests results, common-sense knowledge and patient's clinical profile at the lower level, and correlation rules between health conditions across upper levels. The logical formalization and the reasoning process are based on answer set programming. The expressive power of this logic programming paradigm makes it possible to reason about health evolution even when the available information is incomplete and potentially incoherent, while declarativity simplifies rules specification by caregivers and allows automatic encoding of knowledge. This paper describes how these issues have been targeted in the application scenario of the SINDI system.
In a ubiquitous system, there are several interacting computational objects which use each others' resources. As the number of resources and their consumers grow in such systems, the delay that the consumers exper...
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ISBN:
(纸本)9783642228759
In a ubiquitous system, there are several interacting computational objects which use each others' resources. As the number of resources and their consumers grow in such systems, the delay that the consumers experience for obtaining control over resources increases with an existing rule-based resource allocation technique. Distributing the resource allocation, however, complicates the nature of deadlocks that may arise and requires more sophisticated techniques as compared to a setup with central control. The goal of this paper is to generalize the current resource allocation method to a distributed setting and, in particular, to propose an approach for handling deadlocks in this case.
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