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    Self assessment schemes for multi-agent cooperative search

    Sujit, P.B. ; Ghose, D.
    American Control Conference, 2006

    Digital Object Identifier: 10.1109/ACC.2006.1656411
    Publication Year: 2006
    Cited by 1

    IEEE Conference Publications

    In this paper, we present self assessment schemes (SAS) for multiple agents performing a search mission on an unknown terrain. The agents are subjected to limited communication and sensor ranges. The agents communicate and coordinate with their neighbours to arrive at route decisions. The self assessment schemes proposed here have very low communication and computational overhead. The SAS also has attractive features like scalability to large number of agents and fast decision-making capability. SAS can be used with partial or complete information sharing schemes during the search mission. We validate the performance of SAS using simulation on a large search space consisting of 100 agents with different information structures and self assessment schemes. We also compare the results obtained using SAS with that of a previously proposed negotiation scheme. The simulation results show that the SAS is scalable to large number of agents and can perform as good as the negotiation schemes with reduced communication requirement (almost 20 % of that required for negotiation) View full abstract»

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    Self Assessment-Based Decision Making for Multiagent Cooperative Search

    Sujit, P.B. ; Ghose, D.
    Automation Science and Engineering, IEEE Transactions on

    Volume: 8 , Issue: 4
    Digital Object Identifier: 10.1109/TASE.2011.2155058
    Publication Year: 2011 , Page(s): 705 - 719

    IEEE Journals & Magazines

    This paper addresses a search problem with multiple limited capability search agents in a partially connected dynamical networked environment under different information structures. A self assessment-based decision-making scheme for multiple agents is proposed that uses a modified negotiation scheme with low communication overheads. The scheme has attractive features of fast decision-making and scalability to large number of agents without increasing the complexity of the algorithm. Two models of the self assessment schemes are developed to study the effect of increase in information exchange during decision-making. Some analytical results on the maximum number of self assessment cycles, effect of increasing communication range, completeness of the algorithm, lower bound and upper bound on the search time are also obtained. The performance of the various self assessment schemes in terms of total uncertainty reduction in the search region, using different information structures is studied. It is shown that the communication requirement for self assessment scheme is almost half of the negotiation schemes and its performance is close to the optimal solution. Comparisons with different sequential search schemes are also carried out. View full abstract»

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