1. THe University of Georgia Genetic Algorithm BOT
Thuggabot
THe University of Georgia Genetic Algorithm BOT

2. Thuggabot Half-Life Game World Thuggabot Concepts Combat Strategy
Genetic Algorithm Learning
Test Results
Demo

3. Half-Life Game World First-Person Shooter (3D Environment)
Objective: Maximize kills, Minimize Deaths
Upon dying, players re-spawn with minimal equipment.
Throughout the game, players gather items to help them accomplish goals.

4. Thuggabot Concepts AI Combat Agent Acts to simulate human player
Goal Oriented
Utilizes Genetic Algorithm
Based on the HPB Bot Framework by Botman

5. Combat Strategy Each bot has preferences regarding possible actions
Bots choose goals based on preferences
Bots which make good choices are more effective in combat
Bots adapt to their environment through evolution.

6. Genetic Algorithms Representation
Array of weights that correspond to actions and weapon preferences
Proportional Fitness Tournament Selection
Uniform Crossover
Random Index Mutation

7. Test Results Roughly monotone increasing performance
Some goals clearly become favored over others
Some preferences fluctuate due to dynamic nature of the environment.
Tested against TheFatal’s “Jumbot,” Thuggabot achieved long-term domination