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Multiagent-Based Approach for Risk Analysis in Mission Capability Planning

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Agent-Based Evolutionary Search

Part of the book series: Adaptation, Learning, and Optimization ((ALO,volume 5))

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Abstract

In this chapter, we propose a multiagent-based approach for risk analysis in military capability planning. A hierarchical system is introduced that has two layers: an Option Production Layer (OPL) to find all possible options for the given planning problem, and a Risk Tolerance Layer (RTL) in which DMs’ acceptance of risk is evolved. The OPL uses metaheuristic techniques such as evolutionary algorithms to deal with multi-objectivity of a class of NP-hard resource investment problems, called the Mission Capability Planning Problem (MCPP), under the presence of risk factors. This problem has at least two inherent conflicting objectives: minimizing the cost of investment in resources as well as optimizing the makespan of plans. The framework allows for the addition of a risk-based objective to the problem in order to support risk assessment during the planning process. The RTL is run by a multi-agent system which simulates the risk attitudes of DM. The system determines different types of attitudes towards risk with each type applying to a sub-set of MCPP solutions. The goal of each agent is to maximize its risk tolerance levels with respect to a given subset of solutions determined in the OPL. Risk tolerance levels are used as surrogates for risk attitudes. The hierarchical system is flexible in terms of using a feedback mechanism when necessary. The RTL uses information from the OPL and can itself return some hyper-information to guide the OPL further. In a case study, we use a mission planning scenario to validate our proposal. The results from this study demonstrate the advantage of our proposed system. A diverse set of agents was found; hence different types of options can be grouped and offered to the decision-makers.

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Author information

Authors and Affiliations

  1. School of SEIT, University College, University of New South Wales, Canberra, Australia

    Lam T. Bui, Michael Barlow & Hussein A. Abbass

  2. Defence Science and Technology Organisation (DSTO), Edinburgh, South Australia, Australia

    Axel Bender

Authors
  1. Lam T. Bui
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  2. Axel Bender
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  3. Michael Barlow
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  4. Hussein A. Abbass
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Editors and Affiliations

  1. School of Engineering and Information Technology, University of New SouthWales , ADFA Campus, Northcott Drive, 2600, Canberra, ACT, Australia

    Ruhul Amin Sarker  & Tapabrata Ray  & 

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Bui, L.T., Bender, A., Barlow, M., Abbass, H.A. (2010). Multiagent-Based Approach for Risk Analysis in Mission Capability Planning. In: Sarker, R.A., Ray, T. (eds) Agent-Based Evolutionary Search. Adaptation, Learning, and Optimization, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13425-8_4

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  • DOI: https://doi.org/10.1007/978-3-642-13425-8_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13424-1

  • Online ISBN: 978-3-642-13425-8

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