This decommissioned ERA site remains active temporarily to support our final migration steps to https://ualberta.scholaris.ca, ERA's new home. All new collections and items, including Spring 2025 theses, are at that site. For assistance, please contact erahelp@ualberta.ca.
Search
Skip to Search Results- 2Monte-Carlo Tree Search
- 1AI
- 1Artificial intelligence
- 1Board games
- 1Computer games
- 1Deep Reinforcement Learning
-
Spring 2012
Havannah is a recent game that is interesting from an AI research perspective. Some of its properties, including virtual connections, frames, dead cells, draws and races to win, are explained. Monte Carlo Tree Search (MCTS) is well suited to play Havannah, but many improvements are possible....
-
Spring 2020
Single-agent optimization tasks, also referred to as single-player games, include any domain with an agent whose goal is to maximize an objective function(s), without interference from any other agents. Such tasks have been studied for decades. For example, in 2006, NASA automated the design of...