Artificial Intelligence (AI) approaches to problem-solving and decision-making are becoming more and more complex, leading to a decrease in the understandability of solutions. The European Union’s new General Data Pr...
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programming environments have evolved from purely text based to using graphical user interfaces, and now we see a move towards web based interfaces, such as Jupyter. Web based interfaces allow for the creation of inte...
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This paper describes how XSB combines top-down and bottom-up computation through the mechanisms of variant tabling and subsumptive tabling with abstraction, respectively. It is well known that top-down evaluation of l...
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Management of chronic diseases, such as heart failure, is a major public health problem. A standard approach to managing chronic diseases by medical community is to have a committee of experts develop guidelines that ...
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Management of chronic diseases, such as heart failure, is a major public health problem. A standard approach to managing chronic diseases by medical community is to have a committee of experts develop guidelines that all physicians should follow. Due to their complexity, these guidelines are difficult to implement and are adopted slowly by the medical community at large. We have developed a physician advisory system that codes the entire set of clinical practice guidelines for managing heart failure using answer set programming. In this paper, we show how abductive reasoning can be deployed to find missing symptoms and conditions that the patient must exhibit in order for a treatment prescribed by a physician to work effectively. Thus, if a physician does not make an appropriate recommendation or makes a non-adherent recommendation, our system will advise the physician about symptoms and conditions that must be in effect for that recommendation to apply. It is under consideration for acceptance in TPLP.
We describe an optimization application in the context of steel manufacturing, to design and schedule batches for annealing furnaces. Our solution approach uses a two-phase decomposition. The first phase groups togeth...
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ISBN:
(纸本)9783319661582;9783319661575
We describe an optimization application in the context of steel manufacturing, to design and schedule batches for annealing furnaces. Our solution approach uses a two-phase decomposition. The first phase groups together orders into batches using a mixed-integer linear programming model. The second phase assigns the batches to furnaces and schedules them over time, using constraint programming. Our solution has been developed for operational use in two plants of a steel manufacturer in North America.
The causal rejection-based update semantics assign meanings to a Dynamic logic Program (DLP), which is a sequence of logic programs each one updating the preceding ones. Although there are translations of DLPs under t...
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ISBN:
(纸本)9783319616605;9783319616599
The causal rejection-based update semantics assign meanings to a Dynamic logic Program (DLP), which is a sequence of logic programs each one updating the preceding ones. Although there are translations of DLPs under these update semantics to logic programs of Answer Set programming (ASP), they have not led to efficient and easy to use implementations. This is mainly because such translations aim offline solving in a sense that the resulting logic program is given to an answer set solver to compute models of the current DLP and for any future updates the whole process has to be repeated from scratch. We aim to remedy this situation by utilizing multi-shot ASP, composed of iterative answer set computations of a changing program without restarting from scratch at every step. To this end, we developed a system called moviola, utilizing the multi-shot answer set solver clingo. Using the system, a user can interactively write a DLP, update it, compute its models according to various semantics on the fly.
We introduce a parallel offline algorithm for computing hybrid conditional plans, called HCP-ASP, oriented towards robotics applications. HCP-ASP relies on modeling actuation actions and sensing actions in an expressi...
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We introduce a parallel offline algorithm for computing hybrid conditional plans, called HCP-ASP, oriented towards robotics applications. HCP-ASP relies on modeling actuation actions and sensing actions in an expressive nonmonotonic language of answer set programming (ASP), and computation of the branches of a conditional plan in parallel using an ASP solver. In particular, thanks to external atoms, continuous feasibility checks (like collision checks) are embedded into formal representations of actuation actions and sensing actions in ASP;and thus each branch of a hybrid conditional plan describes a feasible execution of actions to reach their goals. Utilizing nonmonotonic constructs and nondeterministic choices, partial knowledge about states and nondeterministic effects of sensing actions can be explicitly formalized in ASP;and thus each branch of a conditional plan can be computed by an ASP solver without necessitating a conformant planner and an ordering of sensing actions in advance. We apply our method in a service robotics domain and report experimental evaluations. Furthermore, we present performance comparisons with other compilation based conditional planners on standardized benchmark domains.
The natural way to use Answer Set programming (ASP) to represent knowledge in Artificial Intelligence or to solve a combinatorial problem is to elaborate a first-order logic program with default negation. In a prelimi...
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The natural way to use Answer Set programming (ASP) to represent knowledge in Artificial Intelligence or to solve a combinatorial problem is to elaborate a first-order logic program with default negation. In a preliminary step, this program with variables is translated in an equivalent propositional one by a first tool: the grounder. Then, the propositional program is given to a second tool: the solver. This last one computes (if they exist) one or many answer sets (stable models) of the program, each answer set encoding one solution of the initial problem. Until today, almost all ASP systems apply this two steps computation. In this article, the project ASPeRiX is presented as a first-order forward chaining approach for Answer Set Computing. This project was among the first to introduce an approach of answer set computing that escapes the preliminary phase of rule instantiation by integrating it in the search process. The methodology applies a forward chaining of first-order rules that are grounded on the fly by means of previously produced atoms. Theoretical foundations of the approach are presented, the main algorithms of the ASP solver ASPeRiX are detailed and some experiments and comparisons with existing systems are provided.
A complete classification of the complexity of the local and global satisfiability problems for graded modal language over traditional classes of frames have already been established. By"traditional" classes...
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Researchers in answer set programming and constraint programming have spent significant efforts in the development of hybrid languages and solving algorithms combining the strengths of these traditionally separate fie...
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Researchers in answer set programming and constraint programming have spent significant efforts in the development of hybrid languages and solving algorithms combining the strengths of these traditionally separate fields. These efforts resulted in a new research area: constraint answer set programming. Constraint answer set programming languages and systems proved to be successful at providing declarative, yet efficient solutions to problems involving hybrid reasoning tasks. One of the main contributions of this paper is the first comprehensive account of the constraint answer set language and solver ezcsp, a mainstream representative of this research area that has been used in various successful applications. We also develop an extension of the transition systems proposed by Nieuwenhuis et al. in 2006 to capture Boolean satisfiability solvers. We use this extension to describe the ezcsp algorithm and prove formal claims about it. The design and algorithmic details behind ezcsp clearly demonstrate that the development of the hybrid systems of this kind is challenging. Many questions arise when one faces various design choices in an attempt to maximize system's benefits. One of the key decisions that a developer of a hybrid solver makes is settling on a particular integration schema within its implementation. Thus, another important contribution of this paper is a thorough case study based on ezcsp, focused on the various integration schemas that it provides.
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