26,515 research outputs found
Tools of the Trade: A Survey of Various Agent Based Modeling Platforms
Agent Based Modeling (ABM) toolkits are as diverse as the community of people who use them. With so many toolkits available, the choice of which one is best suited for a project is left to word of mouth, past experiences in using particular toolkits and toolkit publicity. This is especially troublesome for projects that require specialization. Rather than using toolkits that are the most publicized but are designed for general projects, using this paper, one will be able to choose a toolkit that already exists and that may be built especially for one's particular domain and specialized needs. In this paper, we examine the entire continuum of agent based toolkits. We characterize each based on 5 important characteristics users consider when choosing a toolkit, and then we categorize the characteristics into user-friendly taxonomies that aid in rapid indexing and easy reference.Agent Based Modeling, Individual Based Model, Multi Agent Systems
The SP theory of intelligence: benefits and applications
This article describes existing and expected benefits of the "SP theory of
intelligence", and some potential applications. The theory aims to simplify and
integrate ideas across artificial intelligence, mainstream computing, and human
perception and cognition, with information compression as a unifying theme. It
combines conceptual simplicity with descriptive and explanatory power across
several areas of computing and cognition. In the "SP machine" -- an expression
of the SP theory which is currently realized in the form of a computer model --
there is potential for an overall simplification of computing systems,
including software. The SP theory promises deeper insights and better solutions
in several areas of application including, most notably, unsupervised learning,
natural language processing, autonomous robots, computer vision, intelligent
databases, software engineering, information compression, medical diagnosis and
big data. There is also potential in areas such as the semantic web,
bioinformatics, structuring of documents, the detection of computer viruses,
data fusion, new kinds of computer, and the development of scientific theories.
The theory promises seamless integration of structures and functions within and
between different areas of application. The potential value, worldwide, of
these benefits and applications is at least $190 billion each year. Further
development would be facilitated by the creation of a high-parallel,
open-source version of the SP machine, available to researchers everywhere.Comment: arXiv admin note: substantial text overlap with arXiv:1212.022
Performance Analysis of Open Source Machine Learning Frameworks for Various Parameters in Single-Threaded and Multi-Threaded Modes
The basic features of some of the most versatile and popular open source
frameworks for machine learning (TensorFlow, Deep Learning4j, and H2O) are
considered and compared. Their comparative analysis was performed and
conclusions were made as to the advantages and disadvantages of these
platforms. The performance tests for the de facto standard MNIST data set were
carried out on H2O framework for deep learning algorithms designed for CPU and
GPU platforms for single-threaded and multithreaded modes of operation Also, we
present the results of testing neural networks architectures on H2O platform
for various activation functions, stopping metrics, and other parameters of
machine learning algorithm. It was demonstrated for the use case of MNIST
database of handwritten digits in single-threaded mode that blind selection of
these parameters can hugely increase (by 2-3 orders) the runtime without the
significant increase of precision. This result can have crucial influence for
optimization of available and new machine learning methods, especially for
image recognition problems.Comment: 15 pages, 11 figures, 4 tables; this paper summarizes the activities
which were started recently and described shortly in the previous conference
presentations arXiv:1706.02248 and arXiv:1707.04940; it is accepted for
Springer book series "Advances in Intelligent Systems and Computing
ISICSoo: a class for the calculation of ionization cross sections from ECPSSR and PWBA theory
ISICS, originally a C language program for calculating K-, L- and M-shell
ionization and X-ray production cross sections from ECPSSR and PWBA theory, has
been reengineered into a C++ language class, named ISICSoo. The new software
design enables the use of ISICS functionality in other software systems. The
code, originally developed for Microsoft Windows operating systems, has been
ported to Linux and Mac OS platforms to facilitate its use in a wider
scientific environment. The reengineered software also includes some fixes to
the original implementation, which ensure more robust computational results and
a review of some physics parameters used in the computation. The paper
describes the software design and the modifications to the implementation with
respect to the previous version; it also documents the test process and
provides some indications about the software performance.Comment: Preprint submitted to Computer Physics Communication
Applications of MATLAB in Natural Sciences: A Comprehensive Review
In the natural sciences, MATLAB is a versatile and essential tool that has revolutionized research across various disciplines, including physics, chemistry, biology, geology, and environmental sciences. This review paper provides a comprehensive overview of MATLAB's applications in data analysis, modeling, simulation, image processing, computational chemistry, environmental sciences, physics, engineering, and data visualization. MATLAB simplifies data analysis by handling complex datasets, performing statistical analyses, and aiding in tasks like curve fitting and spectral analysis. In modeling and simulation, it enables the creation of predictive models for intricate systems, facilitating simulations of physical processes, ecological dynamics, and chemical reactions. In image processing, MATLAB enhances and analyzes images, benefiting fields such as medical imaging and remote sensing. For computational chemistry, MATLAB offers a rich library of tools for exploring molecular structures and simulating chemical reactions. Environmental sciences rely on MATLAB for climate data analysis and ecological modeling. In physics and engineering, it is invaluable for simulating complex systems and analyzing experimental data. Additionally, MATLAB's data visualization capabilities allow scientists to create compelling visuals for effective communication. While challenges like licensing costs exist, efforts are underway to address these issues and enhance integration with other software, including artificial intelligence and machine learning tools. Overall, MATLAB's computational power and versatility are fundamental to advancing natural sciences research, making it an invaluable resource for scientists and researchers across various disciplines
Ten Quick Tips for Using a Raspberry Pi
Much of biology (and, indeed, all of science) is becoming increasingly
computational. We tend to think of this in regards to algorithmic approaches
and software tools, as well as increased computing power. There has also been a
shift towards slicker, packaged solutions--which mirrors everyday life, from
smart phones to smart homes. As a result, it's all too easy to be detached from
the fundamental elements that power these changes, and to see solutions as
"black boxes". The major goal of this piece is to use the example of the
Raspberry Pi--a small, general-purpose computer--as the central component in a
highly developed ecosystem that brings together elements like external
hardware, sensors and controllers, state-of-the-art programming practices, and
basic electronics and physics, all in an approachable and useful way. External
devices and inputs are easily connected to the Pi, and it can, in turn, control
attached devices very simply. So whether you want to use it to manage
laboratory equipment, sample the environment, teach bioinformatics, control
your home security or make a model lunar lander, it's all built from the same
basic principles. To quote Richard Feynman, "What I cannot create, I do not
understand".Comment: 12 pages, 2 figure
Towards an Intelligent Database System Founded on the SP Theory of Computing and Cognition
The SP theory of computing and cognition, described in previous publications,
is an attractive model for intelligent databases because it provides a simple
but versatile format for different kinds of knowledge, it has capabilities in
artificial intelligence, and it can also function like established database
models when that is required.
This paper describes how the SP model can emulate other models used in
database applications and compares the SP model with those other models. The
artificial intelligence capabilities of the SP model are reviewed and its
relationship with other artificial intelligence systems is described. Also
considered are ways in which current prototypes may be translated into an
'industrial strength' working system
PaPaS: A Portable, Lightweight, and Generic Framework for Parallel Parameter Studies
The current landscape of scientific research is widely based on modeling and
simulation, typically with complexity in the simulation's flow of execution and
parameterization properties. Execution flows are not necessarily
straightforward since they may need multiple processing tasks and iterations.
Furthermore, parameter and performance studies are common approaches used to
characterize a simulation, often requiring traversal of a large parameter
space. High-performance computers offer practical resources at the expense of
users handling the setup, submission, and management of jobs. This work
presents the design of PaPaS, a portable, lightweight, and generic workflow
framework for conducting parallel parameter and performance studies. Workflows
are defined using parameter files based on keyword-value pairs syntax, thus
removing from the user the overhead of creating complex scripts to manage the
workflow. A parameter set consists of any combination of environment variables,
files, partial file contents, and command line arguments. PaPaS is being
developed in Python 3 with support for distributed parallelization using SSH,
batch systems, and C++ MPI. The PaPaS framework will run as user processes, and
can be used in single/multi-node and multi-tenant computing systems. An example
simulation using the BehaviorSpace tool from NetLogo and a matrix multiply
using OpenMP are presented as parameter and performance studies, respectively.
The results demonstrate that the PaPaS framework offers a simple method for
defining and managing parameter studies, while increasing resource utilization.Comment: 8 pages, 6 figures, PEARC '18: Practice and Experience in Advanced
Research Computing, July 22--26, 2018, Pittsburgh, PA, US
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