List of Tables

Chapter 2. Go as a machine-learning problem

Table 2.1. Approximate number of possible board states in games

Table 2.2. Traditional Go ranks

Chapter 4. Playing games with tree search

Table 4.1. Classifying board and card games

Chapter 10. Reinforcement learning with policy gradients

Table 10.1. Policy-learning troubleshooting

Chapter 13. AlphaGo: Bringing it all together

Table 13.1. Feature planes used in AlphaGo

Chapter 14. AlphaGo Zero: Integrating tree search with reinforcement learning

Table 14.1. Comparing tree-search algorithms

Table 14.2. Choosing a branch to follow

Appendix A. Mathematical foundations

Table A.1. Examples of derivatives