5,706 research outputs found

    The Multi-engine ASP Solver ME-ASP: Progress Report

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    MEASP is a multi-engine solver for ground ASP programs. It exploits algorithm selection techniques based on classification to select one among a set of out-of-the-box heterogeneous ASP solvers used as black-box engines. In this paper we report on (i) a new optimized implementation of MEASP; and (ii) an attempt of applying algorithm selection to non-ground programs. An experimental analysis reported in the paper shows that (i) the new implementation of \measp is substantially faster than the previous version; and (ii) the multi-engine recipe can be applied to the evaluation of non-ground programs with some benefits

    Pedagogical Possibilities for the N-Puzzle Problem

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    In this paper we present work on a project funded by the National Science Foundation with a goal of unifying the Artificial Intelligence (AI) course around the theme of machine learning. Our work involves the development and testing of an adaptable framework for the presentation of core AI topics that emphasizes the relationship between AI and computer science. Several hands-on laboratory projects that can be closely integrated into an introductory AI course have been developed. We present an overview of one of the projects and describe the associated curricular materials that have been developed. The project uses machine learning as a theme to unify core AI topics in the context of the N-puzzle game. Games provide a rich framework to introduce students to search fundamentals and other core AI concepts. The paper presents several pedagogical possibilities for the N-puzzle game, the rich challenge it offers, and summarizes our experiences using it

    An Analysis of Interaction Design in Children's Games Based on Computational Thinking

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    INTRODUCTION: Several digital games that aim at developing computational thinking in children have emerged in the last few years, as the importance of such ability is increasingly being recognized. Nevertheless, there are no appropriate methods to determine the quality of these games, which hinders their adoption in formal education settings. OBJECTIVES: The general goal of this research is to contribute to the development of a specific evaluation method for children's games that involve computational thinking. In this sense, the specific objective of this paper is to identify which pedagogical and technical aspects of children's interaction with this type of game are proved relevant for developing computational thinking. METHODS: An analysis of two games based on the logic of programming was performed through empirical observation of children's exploratory interaction, in the light of heuristics for interface usability, consisting thus of a combination of formative and objective evaluation. RESULTS: Analysis showed that the game's environment for experimenting with programming commands and visualizing the consequent effects was not sufficient for effective guidance, revealing the need for a human mediator. The main aspects identified as needing improvement were the forms of instruction provided to the child; the design of visual representations of commands, which embed key logical concepts; the correspondence between children's context and expectations and the games' simulated world. CONCLUSION: Results point to directions for the creation of specific parameters and adapted heuristics for evaluation of games based on programming logic for children. In particular the main open question is how to design a game so that computational thinking concepts are implicit conditions to solve challenges, making the process engaging but above all leading to the construction of complex concepts such as parameterized commands

    Credimus

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    We believe that economic design and computational complexity---while already important to each other---should become even more important to each other with each passing year. But for that to happen, experts in on the one hand such areas as social choice, economics, and political science and on the other hand computational complexity will have to better understand each other's worldviews. This article, written by two complexity theorists who also work in computational social choice theory, focuses on one direction of that process by presenting a brief overview of how most computational complexity theorists view the world. Although our immediate motivation is to make the lens through which complexity theorists see the world be better understood by those in the social sciences, we also feel that even within computer science it is very important for nontheoreticians to understand how theoreticians think, just as it is equally important within computer science for theoreticians to understand how nontheoreticians think

    A generic framework for context-sensitive analysis of modular programs

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    Context-sensitive analysis provides information which is potentially more accurate than that provided by context-free analysis. Such information can then be applied in order to validate/debug the program and/or to specialize the program obtaining important improvements. Unfortunately, context-sensitive analysis of modular programs poses important theoretical and practical problems. One solution, used in several proposals, is to resort to context-free analysis. Other proposals do address context-sensitive analysis, but are only applicable when the description domain used satisfies rather restrictive properties. In this paper, we argĂĽe that a general framework for context-sensitive analysis of modular programs, Le., one that allows using all the domains which have proved useful in practice in the non-modular setting, is indeed feasible and very useful. Driven by our experience in the design and implementation of analysis and specialization techniques in the context of CiaoPP, the Ciao system preprocessor, in this paper we discuss a number of design goals for context-sensitive analysis of modular programs as well as the problems which arise in trying to meet these goals. We also provide a high-level description of a framework for analysis of modular programs which does substantially meet these objectives. This framework is generic in that it can be instantiated in different ways in order to adapt to different contexts. Finally, the behavior of the different instantiations w.r.t. the design goals that motivate our work is also discussed
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