804 research outputs found
A Critical Look at the Abstraction Based on Macro-Operators
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
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
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
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
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
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
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
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
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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