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Generating Maximal Domino Patterns by Cellular Automata Agents

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 10421)

Abstract

Considered is a 2D cellular automaton with moving agents. The objective is to find agents controlled by a Finite State Program (FSP) that can form domino patterns. The quality of a formed pattern is measured by the degree of order computed by counting matching \(3 \times 3\) patterns (templates). The class of domino patterns is defined by four templates. An agent reacts on its own color, the color in front, and whether it is blocked or not. It can change the color, move or not, and turn into any direction. Four FSP were evolved for multi-agent systems with 1, 2, 4 agents initially placed in the corners of the field. For a \(12 \times 12\) training field the aimed pattern could be formed with a 100% degree of order. The performance was also high with other field sizes. Livelocks are avoided by using three different variants of the evolved FSP. The degree of order usually fluctuates after reaching a certain threshold, but it can also be stable, and the agents may show the termination by running in a cycle, or by stopping their activity.

Keywords

  • Cellular automata agents
  • Multi-agent system
  • Pattern formation
  • Evolving FSM behavior
  • Spatial computing

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Correspondence to Dominique Désérable .

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Hoffmann, R., Désérable, D. (2017). Generating Maximal Domino Patterns by Cellular Automata Agents. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 2017. Lecture Notes in Computer Science(), vol 10421. Springer, Cham. https://doi.org/10.1007/978-3-319-62932-2_2

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  • DOI: https://doi.org/10.1007/978-3-319-62932-2_2

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