Abstract
Given a 2d Cellular Automaton (CA) with mobile agents controlled by a finite state automaton (algorithm). Initially the field is colored white and agents are randomly placed. They have the task to color the whole field into black in shortest time. The objective is to find algorithms that (1) can form the black–pattern, (2) keep it stable and then (3) change into a global state where all agents stop their activity. Four levels of stability are distinguished, depending on the grade of inactivity after having formed the pattern. For systems with up to four agents we found such algorithms by applying genetic algorithms (GA) and manual post fine tuning. Performances and simulations of these algorithms are presented.
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Notes
- 1.
The GA method was very time consuming (millions of multi-agent simulations) and took around 4 weeks of computation time on a state–of–the–art quad-core PC 3.5 GHz.
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Hoffmann, R., Désérable, D., Seredyński, F. (2018). Termination and Stability Levels in Evolved CA Agents for the Black–Pattern Task. In: Mauri, G., El Yacoubi, S., Dennunzio, A., Nishinari, K., Manzoni, L. (eds) Cellular Automata. ACRI 2018. Lecture Notes in Computer Science(), vol 11115. Springer, Cham. https://doi.org/10.1007/978-3-319-99813-8_12
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