This problem had two aspects: automatically generating correct KenKen boards, given certain requirements as inputs, and generating meaningful feedback for common student errors. The secondary focus of the project was to automate the grading of the Constraint Satisfaction Problem assignment, which revolves around solving KenKen boards. This enables the teaching team to automatically assess whether a student’s submission is equivalent to the correct solution template. To identify when two problem and domain pairs are isomorphic. The primary focus of the project was the automation of the PDDL Assignment grading, by devising a script using the Python tarski library Several assignments in the CISC352 Introduction to AI course are very time-consuming to mark by the teaching team, and the overall purpose of this project was to automate this process.

Both the PDDL and CSP components were run on student submissions from the CISC352 course and effectively reduced marking time for the teaching team. The automation process for this assignment involved automatically generating KenKen boards and outputting meaningful feedback for each student submission. The second component focused on the constraint satisfaction problem (CSP) assignment and involved KenKen boards. The result of this process indicates whether a student’s submission aligns with the reference solution, providing a quick and efficient way to find errors within a student’s submission. This involved creating a script that merged two domain-problem pairs to check for isomorphism. The primary component focused on the grading of the PDDL assignment. This project consisted of two components with the goal of automating the grading process of CISC352 assignments.

Mulab 7 sequence editor