Modified Ant Colony Algorithm For Swarm Multi Agent Exploration on Target Searching in Unknown Environment

The ant colony algorithm (ACA) method basically aims to solve target search problems strategy. In previous researchers, the method of ant colony have been use to solve optimization path to target, where the location of target is known. But this method cannot solve if the position of target is unknown. To solve unknown target, swarm agent can explore entire environment using ant colony algorithm. This research proposed a new method for swarm multi agent exploration on unknown target using modified ant colony algorithm based on Anti-pheromone. First strategy making swarm agent motion move direction, so that swarm agent can avoid the obstacle until find the target and the second by making swarm agent explore the entire environment using Anti-pheromone algorithm for information, the purpose of using Anti-pheromone algorithm is to make ant colony always making of decision to choose a path with a small number of pheromones. The simulated results present that modified algorithm of ant colony system can make swarm agent to explore in searching for find target position while the swarm avoid the obstacle. First simulation with 1-5 agent, using criteria (1) better solution to explore entire node, The second simulation with 1-5 agent, can finding target position more effectively using parameter (2) with minimum iterasi and minimum mileage. Proposed method can effectively enable swarm agent to search unknown target position quickly.