Estimating the task route reliability of mobile agent-based systems using Monte Carlo simulation

In this paper we propose two algorithms for estimating the task route reliability of mobile agent-based systems (MABS), which are based on the conditions of the underlying computer network. In addition, we propose a third algorithm for generating a random static planning strategy for mobile agents. The complexity of mobile agent network systems makes it hard to obtain the task route reliability of the MABS theoretically; instead we estimate it using Monte Carlo simulation. In this paper, we assume that the MABS consists of a number of independent mobile agents operating simultaneously. The results we have achieved demonstrate the robustness of the proposed algorithms.

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