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Obstacle avoidance is an extremely important task in swarm robotics as it saves robots from hitting objects and being damaged. A Genetic algorithm can be used to teach robots how to avoid obstacles in different environments. However the evaluation module of this genetic algorithm can be very time consuming module as each candidate solution should be evaluated N times. This paper explains the methodology...