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Publication - Professor Jonathan Lawry

    Exploiting Vagueness for Multi-Agent Consensus


    Crosscombe, M & Lawry, J, 2016, ‘Exploiting Vagueness for Multi-Agent Consensus’. in: Quan Bai, Fenghui Ren, Katsuhide Fujita, Minjie Zhang, Takayuki Ito (eds) Multi-agent and Complex Systems: Post-proceedings of the 2nd International Workshop on Smart Simulation and Modelling for Computer Systems (SSMCS 2015). Springer, Singapore, pp. 67-78


    A framework for consensus modelling is introduced using Kleene’s three
    valued logic as a means to express vagueness in agents’ beliefs.
    Explicitly borderline cases are inherent to propositions involving vague
    concepts where sentences of a propositional language may be absolutely true, absolutely false or borderline.
    By exploiting these intermediate truth values, we can allow agents to
    adopt a more vague interpretation of underlying concepts in order to
    weaken their beliefs and reduce the levels of inconsistency, so as to
    achieve consensus. We consider a consensus combination operation which
    results in agents adopting the borderline truth value as a shared
    viewpoint if they are in direct conflict. Simulation experiments are
    presented which show that applying this operator to agents chosen at
    random (subject to a consistency threshold) from a population, with
    initially diverse opinions, results in convergence to a smaller set of
    more precise shared beliefs. Furthermore, if the choice of agents for
    combination is dependent on the payoff of their beliefs, this acting as a
    proxy for performance or usefulness, then the system converges to
    beliefs which, on average, have higher payoff.

    Full details in the University publications repository