Here, we developed a multi-agent model to describe dynamical pattern formations using pheromones produced by each agent. We compared the balances between exploitation (one site is visited by many foragers) and exploration (many sites are visited by agents) of two algorithms. In both algorithms, agents linearly reacted to pheromone concentrations within their detection fields and changed detection fields depending on the differences between left and right pheromone concentrations. Thanks to this event, we succeeded in agents to produce ordered pattern formations at macro-levels even though each agent’s reactions to pheromones were set as linear reactions. However, agents could achieve more moderated pattern formations when they occasionally stopped changing detection fields by considering the relationship between global information (pheromone concentrations) and local information (moving directions of others).
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