Shallow Decision-Making Analysis in General Video Game Playing

Bravi，Ivan1; Perez-Liebana，Diego1; Lucas，Simon M.1; Liu，Jialin2

10.1109/CIG.2018.8490365

2018-10-11

2325-4270

2325-4289

978-1-5386-4360-0

IEEE Conference on Computatonal Intelligence and Games, CIG

2018-August

1-8

14-17 Aug. 2018

Maastricht, Netherlands

IEEE Computer Society

The General Video Game AI competitions have been the testing ground for several techniques for game-playing, such as evolutionary computation techniques, tree search algorithms, hyper-heuristic-based or knowledge-based algorithms. So far the metrics used to evaluate the performance of agents have been win ratio, game score and length of games. In this paper we provide a wider set of metrics and a comparison method for evaluating and comparing agents. The metrics and the comparison method give shallow introspection into the agent's decision-making process and they can be applied to any agent regardless of its algorithmic nature. In this work, the metrics and the comparison method are used to measure the impact of the terms that compose a tree policy of an MCTS-based agent, comparing with several baseline agents. The results clearly show how promising such general approach is and how it can be useful to understand the behaviour of an AI agent, in particular, how the comparison with baseline agents can help understanding the shape of the agent decision landscape. The presented metrics and comparison method represent a step toward to more descriptive ways of logging and analysing agent's behaviours.

Artificial general intelligence Game metrics Game-playing agent analysis General video game play

其他

英语

EI

[EP/L015846/1]

20184706125270

Artificial intelligence ; Decision making ; Evolutionary algorithms ; Heuristic algorithms ; Interactive computer graphics ; Knowledge based systems

Computer Software, Data Handling and Applications:723 ; Management:912.2

2-s2.0-85056849336

Scopus

1.School of Electronic Engineering and Computer Science, Queen Mary University of London, ,London,United Kingdom
2.Southern University of Science and Technology, ,Shenzhen,China

Bravi，Ivan,Perez-Liebana，Diego,Lucas，Simon M.,et al. Shallow Decision-Making Analysis in General Video Game Playing[C]:IEEE Computer Society,2018:1-8.