804 research outputs found

    A Critical Look at the Abstraction Based on Macro-Operators

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    Abstraction can be an effective technique for dealing with the complexity of planning tasks. This paper is aimed at assessing and identifying in which cases abstraction can actually speed-up the overall search. In fact, it is well known that the impact of abstraction on the time spent to search for a solution of a planning problem can be positive or negative, depending on several factors -including the number of objects defined in the domain, the branching factor, and the plan length. Experimental results highlight the role of such aspects on the overall performance of an algorithm that performs the search at the ground-level only, and compares them with the ones obtained by enforcing abstraction

    A Parametric Hierarchical Planner for Experimenting Abstraction Techniques

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    This paper presents a parametric system, devised and implemented to perform hierarchical planning by delegating the actual search to an external planner (the "parameter") at any level of abstraction, including the ground one. Aimed at giving a better insight of whether or not the exploitation of abstract spaces can be used for solving complex planning problems, comparisons have been made between instances of the hierarchical planner and their non hierarchical counterparts. To improve the significance of the results, three different planners have been selected and used while performing experiments. To facilitate the setting of experimental environments, a novel semi-automatic technique, used to generate abstraction hierarchies starting from ground-level domain descriptions, is also described

    Energy consumption management in Smart Homes: An M-Bus communication system

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    Energy consumption management in Smart Home environments relies on the implementation of systems of cooperative intelligent objects named Smart Meters. In order for devices to cooperate to smart metering applications' execution, they need to make their information available. In this paper we propose a framework that aims at managing energy consumption of controllable appliances in groups of Smart Homes belonging to the same neighbourhood or condominium. We consider not only electric power distribution, but also alternative energy sources such as solar panels. We define a communication paradigm based on M-Bus for the acquisition of relevant data by managing nodes. We also provide a lightweight algorithm for the distribution of the available alternative power among houses. Performance evaluation of experiments in simulation mode prove that the proposed framework does not jeopardise the lifetime of Smart Meters, particularly in typical situations where managed devices do not continuously turn on and off

    PACMAS: A Personalized, Adaptive, and Cooperative MultiAgent System Architecture

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    In this paper, a generic architecture, designed to support the implementation of applications aimed at managing information among different and heterogeneous sources, is presented. Information is filtered and organized according to personal interests explicitly stated by the user. User pro- files are improved and refined throughout time by suitable adaptation techniques. The overall architecture has been called PACMAS, being a support for implementing Personalized, Adaptive, and Cooperative MultiAgent Systems. PACMAS agents are autonomous and flexible, and can be made personal, adaptive and cooperative, depending on the given application. The peculiarities of the architecture are highlighted by illustrating three relevant case studies focused on giving a support to undergraduate and graduate students, on predicting protein secondary structure, and on classifying newspaper articles, respectively

    VOLMAP: a Large Scale Benchmark for Volume Mappings to Simple Base Domains

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    Correspondences between geometric domains (mappings) are ubiquitous in computer graphics and engineering, both for a variety of downstream applications and as core building blocks for higher level algorithms. In particular, mapping a shape to a convex or star-shaped domain with simple geometry is a fundamental module in existing pipelines for mesh generation, solid texturing, generation of shape correspondences, advanced manufacturing etc. For the case of surfaces, computing such a mapping with guarantees of injectivity is a solved problem. Conversely, robust algorithms for the generation of injective volume mappings to simple polytopes are yet to be found, making this a fundamental open problem in volume mesh processing. VOLMAP is a large scale benchmark aimed to support ongoing research in volume mapping algorithms. The dataset contains 4.7K tetrahedral meshes, whose boundary vertices are mapped to a variety of simple domains, either convex or star-shaped. This data constitutes the input for candidate algorithms, which are then required to position interior vertices in the domain to obtain a volume map. Overall, this yields more than 22K alternative test cases. VOLMAP also comprises tools to process this data, analyze the resulting maps, and extend the dataset with new meshes, boundary maps and base domains. This article provides a brief overview of the field, discussing its importance and the lack of effective techniques. We then introduce both the dataset and its major features. An example of comparative analysis between two existing methods is also present

    Experimenting Abstraction Mechanisms Through an Agent-Based Hierarchical Planner

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    In this paper, an agent-based architecture devised to perform experiments on hierarchical planning is described. The planning activity results from the interaction of a community of agents, some of them being explicitly devoted to embed one or more existing planners. The proposed architecture allows to exploit the characteristics of any external planner, under the hypothesis that a suitable wrapper –in form of planning agent– is provided. An implementation of the architecture, able to embed one planner of the graphplan family, has been used to directly assess whether or not abstraction mechanisms can help to reduce the time complexity of the search on specific domains. Some preliminary experiments are reported, focusing on problems taken from the AIPS 2002, 2000 and 1998 planning competitions. Comparative results, obtained by assessing the performances of the selected planner (used first in a stand-alone configuration and then embedded into the proposed multi-agent architecture), put into evidence that abstraction may significantly speed up the search

    Generating Abstractions from Static Domain Analysis

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    This paper addresses the problem of how to implement a proactive behavior according to a two-tiered (i.e., both theoretical and pragmatic) perspective. Theoretically, we claim that abstraction must be used to render agents able to solve complex problems. Pragmatically, we illustrate a technique devised to generate abstract spaces starting from a “ground” description of the domain being modeled

    Personalized Text Categorization Using a MultiAgent Architecture

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    In this paper, a system able to retrieve contents deemed relevant for the users through a text categorization process, is presented. The system is built exploiting a generic multiagent architecture that supports the implementation of applications aimed at (i) retrieving heterogeneous data spread among different sources (e.g., generic html pages, news, blogs, forums, and databases); (ii) filtering and organizing them according to personal interests explicitly stated by each user; (iii) providing adaptation techniques to improve and refine throughout time the profile of each selected user. In particular, the implemented multiagent system creates personalized press-revies from online newspapers. Preliminary results are encouraging and highlight the effectiveness of the approach

    Deterministic Linear Time Constrained Triangulation using Simplified Earcut

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    Triangulation algorithms that conform to a set of non-intersecting input segments typically proceed in an incremental fashion, by inserting points first, and then segments. Inserting a segment amounts to: (1) deleting all the triangles it intersects; (2) filling the so generated hole with two polygons that have the wanted segment as shared edge; (3) triangulate each polygon separately. In this paper we prove that these polygons are such that all their convex vertices but two can be used to form triangles in an earcut fashion, without the need to check whether other polygon points are located within each ear. The fact that any simple polygon contains at least three convex vertices guarantees the existence of a valid ear to cut, ensuring convergence. Not only this translates to an optimal deterministic linear time triangulation algorithm, but such algorithm is also trivial to implement. We formally prove the correctness of our approach, also validating it in practical applications and comparing it with prior art
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