Algorithm structure for real-time general game playing agents

Abstract

General Game Playing is an examination of AI agents that are designed without any explicit knowledge of a particular game. Instead, they are required to play a variety of games that they have never seen before by merely reading the description of the rules at runtime, without any intervention from a human being. Previous successful agents have concentrated their efforts on turn-based games, employing either generic heuristics or the Monte Carlo/UCT simulation technique. Real-time games have dominated the market in recent years, and as a result, agents that have more reflexibility have emerged as an important area of research. In this paper, the author evaluateswhether or not it is possible to implement the already-existing algorithms into a real-time playing GGP agent, and we present a potential algorithm structure that, on the basis of this evaluation, could be able to solve the challenge.