21 research outputs found

    Generation-free Agent-based Evolutionary Computing

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    AbstractMetaheuristics resulting from the hybridization of multi-agent systems with evolutionary computing are efficient in many optimization problems. Evolutionary multi-agent systems (EMAS) are more similar to biological evolution than classical evolutionary algorithms. However, technological limitations prevented the use of fully asynchronous agents in previous EMAS implementations. In this paper we present a new algorithm for agent-based evolutionary computations. The individuals are represented as fully autonomous and asynchronous agents. Evolutionary operations are performed continuously and no artificial generations need to be distinguished. Our results show that such asynchronous evolutionary operators and the resulting absence of explicit generations lead to significantly better results. An efficient implementation of this algorithm was possible through the use of Erlang technology, which natively supports lightweight processes and asynchronous communication

    The Missing Link! A New Skeleton for Evolutionary Multi-agent Systems in Erlang

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    Evolutionary multi-agent systems (EMAS) play a critical role in many artificial intelligence applications that are in use today. In this paper, we present a new generic skeleton in Erlang for parallel EMAS computations. The skeleton enables us to capture a wide variety of concrete evolutionary computations that can exploit the same underlying parallel implementation. We demonstrate the use of our skeleton on two different evolutionary computing applications: (1) computing the minimum of the Rastrigin function; and (2) solving an urban traffic optimisation problem. We show that we can obtain very good speedups (up to 142.44 ×× the sequential performance) on a variety of different parallel hardware, while requiring very little parallelisation effort.Publisher PDFPeer reviewe

    Agent-Based Models and Platforms for Parallel Evolutionary Algorithms

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    Agent-Based Evolutionary and Immunological Optimization

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    Profile-based architecture of evolutionary MAS

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    A sub-type of multi-agent systems (MAS) called evolutionary ones (EMAS), special in its features and field of application, needs a dedicated architecture that would be more adequate and easier in design and implementation. The proposed architecture uses the notion of a profile which models strategies and goals of an agent with respect to an aspect of its operation. To make a decision, an agent is equipped with an algorithm that coordinates premises determined in its profiles. The paper presents main ideas of the architecture illustrated with an actual realisation of an EMAS solving the multi-objective optimisation problem

    Utrzymanie krytycznych zadań oparte na zarządzaniu kryzysowym w obliczeniowych systemach wieloagentowych

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    In this paper we present a biologically-inspired approach for mission survivability (considered as the capability of fulfilling a task such as computation) that allows the system to be aware of the possible threats or crises that may arise. This approach uses the notion of resources used by living organisms to control their populations. We present the concept of energetic selection in agent-based evolutionary systems as well as the means to manipulate the configuration of the computation according to the crises or user's specific demands.W artykule prezentujemy biologicznie inspirowany mechanizm wspomagający utrzymanie krytycznych zadań (tzw. mission survivability) który umożliwia wykrywanie oraz przeciwdziałanie wybranym zagrożeniom. Przedstawione podejście wzorowane jest na wykorzystywaniu przez żywe organizmy zasobów do kontroli populacji. Prezentujemy koncepcje selekcji energetycznej mającej zastosowanie w ewolucyjnych systemach wieloagentowych (EMAS) oraz sposoby konfiguracji obliczenia w celu przeciwdziałania sytuacjom kryzysowym, według preferencji użytkownika

    Towards an Agent-Based Augmented Cloud

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    In the paper an agent-based framework deployed in hybrid cluster and volunteer computing environment is presented. It utilizes two concepts proposed by the authors: Augmented Cloud and Agent Platform as a Service (AgPaaS). Both concepts are discussed in the context of Cloud Computing as defined by NIST. The key idea of the presented solution is to span the cloud (i.e., computing infrastructure) beyond the data center borders by utilizing web browsers as computational workers. The feasibility of the approach was demonstrated by two prototypes: the first one was based on Java Applets and Adobe Flash, whereas the second one on Microsoft Silverlight. The prototypes were next used to perform simple experiments, mainly related to scalability issues. Selected results from the experiments are discussed in the final part of the paper

    Component-Based Architecture for Systems, Services and Data Integration in Support for Criminal Analysis

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    Criminal analysis processes is based on heterogeneous data processing. To support it, analysts utilize a large set of specialized tools, however they are usually designed to solve a particular problem are often incompatible with other existing tools and systems. Therefore, to fully leverage the existing supporting tools, their technological integration is required. In this paper we present original approach for integrating systems based on the component-driven paradigm. Firstly, a problem of supporting criminal analysis is described with a strong emphasis on the heterogeneity issues. Secondly, some theoretical information about integration is depicted followed by the details of the proposed architecture. Finally, the technological assumptions are discussed and prototype integration based on proposed concept is overviewed. om the experiments are discussed in the final part of the paper
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