This repo is where I'll be doing most of my AI homework. Working together with python and various learning algorithms
aNTiCS game is created and curated by Andrew Nuxoll and various students of the University of Portland AI course.
To run the game, you will need Python 2.7.x and pygame, found here:
Pygame download
Python 2.7.x download
In the terminal/command prompt, simply execute the command python Game.py in the aNTiCS directory.
Your assignment is to create an effective heuristic AI for the Antics game. This assignment should get you thinking about the nature of the challenges of creating an AI.
Your aim is to create a heuristic AI that can reliably defeat the random agent in 9 games out of 10. Your agent should also give a human player a modest challenge. Your agent should be able to play 100 games against the random agent in less than five minutes on a lab computer. In addition, your agent must meet the core criteria (below). The design of this agent is totally up to you.
Informed Search Agent - A* Search
Your assignment is to create an Antics agent that performs a multi-level, heuristically guided search of the Antics state space. This agent evaluates a given state, gives it a score, and then traverses the state tree based on the best available score that it has.
MiniMax Search
Expands upon the agent from HW2 and adds a minimax style scoring. This agent also utilizes alpha-beta pruning to help cut down on resource usage.