General video game playing

General video game playing (GVGP) is the design of artificial intelligence programs to be able to play more than one video game successfully. In recent years, some progress have been made in this area, including programs that can learn to play Atari 2600 games as well as a program that can learn to play NES games.

GVGP could potentially be used to create real video game AI automatically, as well as "to test game environments, including those created automatically using procedural content generation and to find potential loopholes in the gameplay that a human player could exploit". GVGP has also been used to generate game rules, and estimate a game's quality based on Relative Algorithm Performance Profiles (RAPP), which compare the skill differentiation that a game allows between good AI and bad AI.

Since 2014, the General Video Game Playing Competition (GVGAI) has offered a way for researchers and practitioners to test and compare their best general video game playing algorithms. The competition has an associated software framework including a large number of games written in the Video Game Description Language (VGDL). VGDL can be used to describe a game specifically for procedural generation of levels, using Answer Set Programming (ASP) and an Evolutionary Algorithm (EA). GVGP can then be used to test the validity of procedural levels, as well as the difficulty or quality of levels based on how an agent performed.

The games used in GVGP are, for now, often 2 dimensional arcade games, as they are the simplest and easiest to quantify. To simplify the process of creating an AI that can interpret video games, games for this purpose are written in Video Game Description Language (VGDL), which is a coding language using simple semantics and commands that can easily be parsed.

...
Wikipedia