Abstract
In this paper, basic biological immune systems and their responses to external elements to maintain an organism's health state are described. The relationship between immune systems and multi-robot systems are also discussed. The proposed algorithm is based on immune network theories that have many similarities with the multi-robot systems domain. The paper describes a refinement of the memory-based immune network that enhances a robot's action-selection process. The refined model; which is based on the Immune Network T-cell-regulated—with Memory (INT-M) model; is applied onto the dog and sheep scenario. The refinements involves the low-level behaviors of the robot dogs, namely Shepherds' Formation and Shepherds' Approach. The shepherds would form a line behind the group of sheep and also obey a safe zone of each sheep, thus achieving better control of the flock. Simulation experiments are conducted on the Player/Stage platform.
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