Problem statement A person has planned for a hiking trip. He decided to pack things for his trip. He had only a backpack bag with a maximum capacity of 20kg. There are different item types that are deemed desirable; these could include bottles of water, fruits, nuts, sandwiches, and so forth. He had made a priority list of the items that had to be added to the bag. Each item type has a set of two attributes, namely a weight (or volume) and a value that quantifies the level of importance associated with each unit of that type of item. Since the bag has a limited weight (or volume) capacity, the problem of interest is to figure out how to load the bag with a combination of units of the specified types of items that yields the greatest total value. The item's weight and corresponding values are given in the following table. Apply a genetic algorithm to find an optimal ordering of the items which he must include in his bag. Use any appropriate selection methods and justify your design choice of chromosomes. Use a fitness coefficient calculated using the sum of item weights present in the bag. Use the below combination of hyperparameter and interpret your observations No.of.Initial.Population ={4,6} Crossover Type ={ Single Point, Two Point } No.of.Mutation Points ={2,1} No.of.Generations ={1000,5000} Evaluations will be based on the following: 1. Explain the PEAS (Performance measure, Environment, Actuator, Sensor.) for your agent. (20\% marks) 2. Use both the above mentioned algorithm with different combination of the hyperparameters and implement in PYTHON. (20%+20%=40% marks) 3. Print the results of each generations and elect the best offspring at the end of the algorithm for each combination of the hyperparameters. ( 20% marks)