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Computational Intelligence Magazine, IEEE

Issue 1 • Date Feb. 2011

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Displaying Results 1 - 15 of 15
  • [Front cover]

    Page(s): C1
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  • Table of contents

    Page(s): 1
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  • Welcoming the Year of the Rabbit! [Editor's Remarks]

    Page(s): 2 - 3
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  • IEEE CIS VP-Members Activities Vision Statement [Society Briefs]

    Page(s): 4 - 5
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  • 2011 IEEE CIS Awards [Society Briefs]

    Page(s): 5 - 10
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  • [CIS Publication Spotlight]

    Page(s): 11 - 16
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  • Interview with Editor-in-Chief of IEEE Transactions on Fuzzy Systems [Career Profile]

    Page(s): 12 - 16
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  • 2010 IEEE World Congress on Computational Intelligence (2010 IEEE WCCI) [Conference Report]

    Page(s): 17 - 19
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  • Computational Intelligence Applications for Defense [Research Frontier]

    Page(s): 20 - 29
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3057 KB) |  | HTML iconHTML  

    Given the current global security environment, there has been increased interest within the security and defense communities in novel techniques for solving challenging problems. New problems have emerged within the broad areas of security and defense that are difficult to tackle with conventional methods, thus requiring new techniques for detecting and adapting to emerging threats. The purpose of the symposium is to present current and ongoing efforts in computational intelligence as applied to security and defense problems. View full abstract»

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  • Computational Red Teaming: Past, Present and Future

    Page(s): 30 - 42
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2588 KB) |  | HTML iconHTML  

    The combination of Computational Intelligence (CI) techniques "with Multi-Agent Systems (MAS) offers a great deal of opportunities for practitioners and Artificial Intelligence (AI) researchers alike. CI techniques provide the means to search massive spaces quickly; find possible, better or optimum solutions in these spaces; construct algorithms, functions and strategies to control an autonomous entity; find patterns and relationships "within data, information, knowledge or experience; assess risk and identify strategies for risk treatment; and connect the dots to synthesize an overall situational awareness picture that decision makers can utilize. MAS provide the structured, modular, distributed and efficient software environment to simulate systems; the architecture to represent systems and entities naturally; the environment to allow entities to observe, communicate "with, negotiate "with, orient "with respect to, and act upon other entities; the modular representation that allows entities to store and manipulate observations, forming beliefs, desires, goals, plans, and intentions; and the framework to model behavior. By bringing CI and MAS together, we have a powerful computational environment that has the theoretical potential to do many things that one can expect "when attempting to structure, understand, and solve a problem. In this article, we follow two objectives. First, we "will present Computational Red Teaming (CRT) as the state-of-the-art architecture representing the integration of CI techniques and MAS for understanding competition. Second, we "will demonstrate how this integration of MAS and CI benefits practitioners in almost all major application domains by drawing examples from defense, business and engineering. We "will present the evolution of CRT by categorizing the different levels of integrating CI and MAS, and highlighting open research questions pertaining to CRT. View full abstract»

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  • Autonomous Self-Reconfiguration of Modular Robots by Evolving a Hierarchical Mechanochemical Model

    Page(s): 43 - 54
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (5371 KB) |  | HTML iconHTML  

    In this paper, we present a two-layer hierarchical mechanochemical model for self-reconfiguration of modular robots in changing environments. The model, which is inspired by the embryonic development of multi-cellular organisms and chemical morphogenesis, can autonomously generate and form different patterns for modular robots to adapt to environmental changes. Layer 1 of the model utilizes a virtual-cell based mechanochemical model to generate appropriate target patterns (i.e., chemical blueprints) for current environment. Layer 2 is a gene regulatory network (GRN) based controller to -coordinate the modules of modular robots for physically realizing the chemical target pattern defined by the first layer. This hierarchical mechanochemical framework is a distributed system in that each module makes decisions based on its local perceptions. To optimize pattern de-sign of modular robots, the covariance matrix adaptation evolution strategy (CMA-ES) is adopted to evolve the pattern parameters of the mechanochemical model. Simulation results demonstrate that the proposed system is effective and robust in autonomously reconfiguring modular robots to adapt to environmental changes. View full abstract»

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  • Mission-Driven Robotic Intelligent Sensor Agents for Territorial Security

    Page(s): 55 - 67
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2176 KB) |  | HTML iconHTML  

    Territorial security deals with the prevention, detection and response to unauthorized persons and/or goods from crossing a perimeter. It deals with large territories of strategic importance, such as international borders, transportation and critical infrastructure. Multi-agent systems provide flexibility, fault-tolerance, high sensing fidelity, low-cost and rapid deployment. In this paper, we concentrate on the challenges presented in applying the concepts of multi-agent systems to those presented by territorial security. We first introduce the overall system as well as prevalent agent architectures. We then briefly present our novel agent architecture, its experimental embodiment and the virtualized reality model that accepts physical sensor data and updates a global model of the environment in real-time. View full abstract»

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  • Controlling Chaos: Suppression, Synchronization and Chaotification (Zhang, H., et al; 2009) [Book Review]

    Page(s): 68 - 69
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  • [Conference Calendar]

    Page(s): 70
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  • 2012 IEEE WCCI

    Page(s): 71
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Aims & Scope

The IEEE Computational Intelligence Magazine (CIM) publishes peer-reviewed articles that present emerging novel discoveries, important insights, or tutorial surveys in all areas of computational intelligence design and applications, in keeping with the Field of Interest of the IEEE Computational Intelligence Society (IEEE/CIS). 

 

Full Aims & Scope