Nannon: A Nano Backgammon for Machine Learning Research

A newly designed game is introduced, which feels like Backgammon, but has a simplified rule set. Unlike earlier attempts at simplifying the game, Nannon maintains enough features and dynamics of the game to be a good model for studying why certain machine learning systems worked so well on Backgammon. As a model, it should illuminate the relationship between different methods of learning, both symbolic and numeric, including techniques such as inductive inference, neural networks, genetic programming, co-evolutionary learning, and reinforcement learning based on value function approximation. It is also fun to play.

• Type: Conference
• Year: 2005
• Where: CIG
• Authors: Jordan B. Pollack
• Keywords: CIG 2005, Earlier Attempts, Machine Learning Systems, Value Function Approximation