Sciweavers

Share
EVOW
2016
Springer

Online Evolution for Multi-action Adversarial Games

4 years 3 months ago
Online Evolution for Multi-action Adversarial Games
We present Online Evolution, a novel method for playing turn-based multi-action adversarial games. Such games, which include most strategy games, have extremely high branching factors due to each turn having multiple actions. In Online Evolution, an evolutionary algorithm is used to evolve the combination of atomic actions that make up a single move, with a state evaluation function used for fitness. We implement Online Evolution for the turn-based multi-action game Hero Academy and compare it with a standard Monte Carlo Tree Search implementation as well as two types of greedy algorithms. Online Evolution is shown to outperform these methods by a large margin. This shows that evolutionary planning on the level of a single move can be very effective for this sort of problems.
Niels Justesen, Tobias Mahlmann, Julian Togelius
Added 03 Apr 2016
Updated 03 Apr 2016
Type Journal
Year 2016
Where EVOW
Authors Niels Justesen, Tobias Mahlmann, Julian Togelius
Comments (0)
books