Artificial Intelligence for Data technique need your help to solve this lab assignments

In this assignment, you will first answer a written question on CSP, based on the assignment problem mentioned at the lecture. Then you will study the Python implementation of CSP algorithms in the AIME library. Finally, you will use this library to solve the above assignment problem. Task 1: Writing task (max: 5 points) Consider the following instance of a resource assignment problem. There are seven lectures L1, ..., L7 to be given on the same day, with the following time schedule:

There are enough teachers, but only three classrooms: A, B, C. The problem is to find an assignment of classroom to lectures so that lectures that have a temporal overlap are not in the same classroom. Describe how this problem can be cast as a CSP. Say what are the variables, their domains and the constraints. Draw the constraint graph. Show a possible solution. Task 2: Programming task A (max: 10 points) Look at the file csp.py in the AIME GitHub: it contains an implementation of most CSP algorithms in your textbook. Try to understand how these algorithms have been implemented in practice. Familiarize yourself in particular with the map-coloring example: run the backtracking search on the three maps provided (australia, usa, france) and follow how the algorithm solves the problems. Try to run the algorithm with constraint propagation (inference=no_inference, default) and with inference=forward_checking, and observe the changes. A good way to follow the algorithm is to insert print statements in the code of csp.py that show, at each step, what assignment is tried and what values are still available for the variables not yet assigned (look, eg, at the curr_domains variable). Describe the results in your report.

Task 3: Programming task B (max: 10 points) Encode the classroom assignment problem described in Task 1 above as a CSP, and use the functions in csp.py in the AIME GitHub to solve it. Tell in your report how you did it, and show the results. Optional: (max: 5 additional points) Instead of writing the CSP for your assignment problem by hand, you may want to write a nicer end-to-end program that: (1) takes as input the schedule of the lectures, e.g., as a dictionary of tuples of the form ; (2) generates a CSP automatically from this schedule; (3) solves the CSP by calling the appropriate function in csp.py; and (4) prints the solution.

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