Agent-Based Simulation in AgE Framework

Faber, Łukasz; Piętak, Kamil; Byrski, Aleksander; Kisiel-Dorohinicki, Marek

doi:10.1007/978-3-642-28888-3_3

Cited by 15 publications

(7 citation statements)

References 13 publications

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“…It is related to and extends our previous publications regarding the implementation of effective tools for running population-based computational intelligence systems [4], especially using the agent paradigm [5], [6] in both parallel and distributed [7], as well as heterogeneous environments [8].…”

Section: Introductionsupporting

confidence: 53%

Efficient parallel execution of genetic algorithms on Epiphany manycore processor

Faber

Boryczko

2016

Annals of Computer Science and Information Systems

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Abstract-Recent years have seen a growing trend towards the introduction of more advanced manycore processors. On the other hand, there is also a growing popularity for cheap, creditcard-sized, devices offering more and more advanced features and computational power.In this paper we evaluate Parallella -a small board with the Epiphany manycore coprocessor consisting of sixteen MIMD cores connected by a mesh network-on-a-chip. Our tests are based on classical genetic algorithms. We discuss some possible optimizations and issues that arise from the architecture of the board. Although we achieve significant speed improvements, there are issues, such us the limited local memory size and slow memory access, that make the implementation of efficient code for Parallella difficult.

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Section: Introductionsupporting

confidence: 53%

Efficient parallel execution of genetic algorithms on Epiphany manycore processor

Faber

Boryczko

2016

Annals of Computer Science and Information Systems

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“…There are several possibilities how to implement such an agent-based simulation platform. Initially, we test our requirements using the AgE platform [25]. The AgE platform includes two types of agents: heavyweight agents and lightweight ones.…”

Section: Agent-based Componentmentioning

confidence: 99%

Hybrid Architecture For Simulation Of Blood Flow With Foreign Bodies

Faber¹,

Boryczko²,

Kisiel-Dorohinicki³

2014

ECMS 2014 Proceedings Edited By: Flaminio Squazzoni, Fabio Baronio, Claudia Archetti, Marco Castellani

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The new methods of diagnosis are often more sensitive and speed up its process allowing for a more effective treatment. Yet they need to be carefully tested before they can be used in practice. The paper concerns the problems of developing nanorobots, which would circulate in the bloodstream of the human body gathering information about its condition. Simulation of these new ways of diagnosis is the main motivation behind the presented work. Introduction of such nanorobots into the bloodstream puts several requirements on their mechanical properties. Thus, our first goal is to build a model to simulate the blood flow with nanorobots present in the capillary vessels and medium-sized blood vessels. We split it into two separate initial models and implementations. The first one is a simulation of the blood flow using particlebased methods in order to determine the appropriate mechanical parameters of nanorobots and verify their behavior. The second one is a multi-agent simulation that will allow to evaluate the usefulness of the data collected and prototype the system performing functions of nanorobots within the specified constraints.

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“…It is targeted at medium-sized simulation and computational applications, which use multi-agent and computational intelligence paradigms [1], but do not need full FIPA compliancy, and would benefit from a component-based approach and distributed computing capabilities. The presented work is a continuation of the platform presented in [2] and [3]. In this paper, however, we focus on component-orientation and distribution, as well as on the possibilities of the platform with regard to simulational and computational applications.…”

Section: Foundation For Intelligent Physical Agentsmentioning

confidence: 99%

Lightweight Distributed Component-Oriented Multi-Agent Simulation Platform

Krzywicki¹,

Faber²,

Piętak³

et al. 2013

ECMS 2013 Proceedings Edited By: Webjorn Rekdalsbakken, Robin T. Bye, Houxiang Zhang

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Existing solutions for agent-based systems turn out to be limited in some applications, like agent-based computing or simulations, where very large numbers of clearly defined agents interact heavily within a closed system. In those cases, fully-fledged, FIPA 1 compliant environment introduce unnecessary overhead, but simple tools fail to scale when confronted to bigger problems. In this paper, we introduce an alternative agent environment called AgE, targeted at medium-sized simulation and computational applications, which use multi-agent and computational intelligence paradigms, but does not need full FIPA compliancy, and would benefit from a component-based approach and distributed computing capabilities. After giving a short review of selected popular multi-agent platforms, the main features of AgE are presented. Next, some basic usability topics are addressed. Then the most interesting architectural aspects of the platform are discussed. Finally, AgE possibilities are demonstrated with two example applications.

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Agent-Based Simulation in AgE Framework

Cited by 15 publications

References 13 publications

Efficient parallel execution of genetic algorithms on Epiphany manycore processor

Efficient parallel execution of genetic algorithms on Epiphany manycore processor

Hybrid Architecture For Simulation Of Blood Flow With Foreign Bodies

Lightweight Distributed Component-Oriented Multi-Agent Simulation Platform

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