Abstract
We are becoming increasingly dependent on large intercon- nected networks for the control of our resources. One important issue is resource protection strategies in the event of failures and/or attacks. To address this issue we investigated the effectiveness of evolving finite-state machine (FSM) strategies for winning against an adversary in a challenging Competition for Resources simulation. Although preliminary results were promising, unproductive cyclic behavior lowered performance. We then augmented evolution with an algorithm that rapidly detects and removes this cyclic behavior, thereby improving performance dramatically.
The evolution of FSMs is often referred to as “evolutionary programming” or “EP”.
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Spears, W.M., Gordon, D.F. (2000). Evolving Finite-State Machine Strategies for Protecting Resources. In: Raś, Z.W., Ohsuga, S. (eds) Foundations of Intelligent Systems. ISMIS 2000. Lecture Notes in Computer Science(), vol 1932. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39963-1_18
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DOI: https://doi.org/10.1007/3-540-39963-1_18
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