Game AI Pro 3

30

Hierarchical Portfolio Search in Prismata

David Churchill and Michael Buro

30.1    Introduction

30.2    AI Design Goals

30.3    Prismata Gameplay Overview

30.4    Hierarchical Portfolio Search

30.5    Evaluation of HPS Playing Strength

30.6    Conclusion

References

30.1  Introduction

Many unique challenges are faced when trying to write an AI system for a modern online strategy game. Players can control groups of tens or even hundreds of units, each with their own unique properties and strategies, making for a gigantic number of possible actions to consider at any given state of the game. Even state-of-the-art search algorithms such as Monte Carlo Tree Search (MCTS) are unable to cope with such large action spaces, as they typically require ...