QUESTION 3 a) Swarm Intelligence (SI) is an Artificial Intelligence technique that studies the collective behavior in decentralized and self-organized system. Briefly describe ONE (1) example of optimization solution using Swarm Intelligence applied in our life. (6 marks) Answer: b) Ant Colony Optimization (ACO) is a discipline of artificial systems modelled after the behaviour of real ant colonies and are useful in solving discrete optimization problem. Figure below shows the routes for the blue and the green ants starting from point A. The distance between each point are as follows: AB = 8, BC = 16, CD = 13, DE = 16, EF = 15, FA = 17, AD = 11, BE = 20, CF = 14 B F E D i. Calculate the distance for the blue and green ants as stated in the above graph. Show your work (6 marks) Answer: ii. If a new ant arrives, which path will it follow and briefly explain ONE (1) reason why such path is selected by the new ant. (4 marks) Answer: 1 c) Particle Swarm Optimization (PSO) is an algorithm inspired from swarm behavior such as bird flocking and schooling in nature. Explain THREE (3) important behaviors for each particle in the swarm. (9 marks) Answer: QUESTION 3 a) Swarm Intelligence (SI) is an Artificial Intelligence technique that studies the collective behavior in decentralized and self-organized system. Briefly describe ONE (1) example of optimization solution using Swarm Intelligence applied in our life. (6 marks) Answer: b) Ant Colony Optimization (ACO) is a discipline of artificial systems modelled after the behaviour of real ant colonies and are useful in solving discrete optimization problem. Figure below shows the routes for the blue and the green ants starting from point A. The distance between each point are as follows: AB = 8, BC = 16, CD = 13, DE = 16, EF = 15, FA = 17, AD = 11, BE = 20, CF = 14 B F E D i. Calculate the distance for the blue and green ants as stated in the above graph. Show your work (6 marks) Answer: ii. If a new ant arrives, which path will it follow and briefly explain ONE (1) reason why such path is selected by the new ant. (4 marks) Answer: 1 c) Particle Swarm Optimization (PSO) is an algorithm inspired from swarm behavior such as bird flocking and schooling in nature. Explain THREE (3) important behaviors for each particle in the swarm. (9 marks)