Advanced Algorithms

Project: Adversarial Caterpillars

Objective

During this activity, students will be able to:

IMPORTANT

For this programming assignment, students are required to complete all work independently and are not permitted to use AI-assisted tools, such as GitHub Copilot, ChatGPT, Gemini, or similar platforms, to automatically generate code. Using AI tools in this way undermines the learning process and violates academic integrity policies. The purpose of this assignment is to assess your understanding and application of the concepts covered in the course. Failure to comply with these guidelines may result in academic penalties, including but not limited to a lower grade.

If you have any questions about the assignment or need clarification on any concepts, please do not hesitate to visit your instructor during office hours. Rely solely on your own knowledge, the course materials, and any authorized resources provided by the instructor.

Description

This activity must be developed in the pre-assigned teams of two.

Using the Dagor framework, design and implement in Python a player for the caterpillar game (Orugas) that plays by applying an “intelligent” strategy. Make sure to review the Adversarial search chapter from [KOPEC] in order to approach this problem adequately.

The each team’s implementation will compete against the implementations of the other teams in a strategy tournament whose rules are described below.

Tournament Rules

Deliverables

Place in a comment at the top of the equipoN.py source file the authors’ personal information (student ID and name), for example:

#----------------------------------------------------------
# Project: Adversarial Caterpillars
#
# Date: 27-Nov-2024
# Authors:
#           A01770771 James Howlett
#           A01777771 Wade Wilson
#----------------------------------------------------------

Upload Instructions

To deliver the equipoN.py file, please provide the following information:

Request PIN

Only one team member needs to upload the file.

Due date is Wednesday, November 27.