Problem Statement Let us consider carpooling apps like ola/uber app. The agent has to decide at any intermediate node, he can choose the next stop which has the least travel fare per hour The following graph will give the cities with their time and fare. The goal node is G. Note that the edge value from A to B "500/3hr" represents 500 is maximum fare and 3hr is the maximum time taken to reach A to B or vice-versa. Find the path taken by the passenger to reach the goal. 700 B 500/3hr 590/1.5hr 1250/Zhr 500 A 500 1500/3hr 850/3hr D 1000/4hr 650/2hr G 0 600/3hr 700/2hr 2500/3hr E 600 750 Note: 1. Explain the environment of the agent [20% weightage) 2. Find the path and cost with respect to time or fare based on the given problem [60% weightage) 3. Use appropriate data structures and implement a search algorithm to find the path that the agent can visit the cities in the graph in Python. [20% weightage] 4. The starting node has to be taken as input from the user. Problem Statement Let us consider carpooling apps like ola/uber app. The agent has to decide at any intermediate node, he can choose the next stop which has the least travel fare per hour The following graph will give the cities with their time and fare. The goal node is G. Note that the edge value from A to B "500/3hr" represents 500 is maximum fare and 3hr is the maximum time taken to reach A to B or vice-versa. Find the path taken by the passenger to reach the goal. 700 B 500/3hr 590/1.5hr 1250/Zhr 500 A 500 1500/3hr 850/3hr D 1000/4hr 650/2hr G 0 600/3hr 700/2hr 2500/3hr E 600 750 Note: 1. Explain the environment of the agent [20% weightage) 2. Find the path and cost with respect to time or fare based on the given problem [60% weightage) 3. Use appropriate data structures and implement a search algorithm to find the path that the agent can visit the cities in the graph in Python. [20% weightage] 4. The starting node has to be taken as input from the user