Article: Enabling Computers to Play Games Like Humans

Enabling Computers to Play Games Like Humans
Stephen McGlinchey [2004]

This article is a quick mention on how it might be possible to create an AI that behaves like a human.

McGlinchey states that AI players can be written with several different objectives. Some developers aim to develop AI players that are most likely to succeed in a game, others aim at producing players that will make the gaming experience more enjoyable and this means that the AI should behave like a human.

She says that there are two aspects of game AI that affect the gamer's experience: level of performance and style of play. This means that the AI must match the experience level of the player and that it must behave similar to how a human would play (AI players should not have superhuman reactions or be able to move in an impossible manner). Failing to correctly adjust any of those will make the experience less immersive and less enjoyable.

One way of solving this problem is a technique that is being researched called motion capture for AI. Which is basically training the AI with recorded data from human players, a process called GoCap (Game Observation Capture). The trained AI can then mimic the data that was used to train it.

The author suggests using Kohonen's Self Organising Map (SOM) in conjunction with the GoCap. In a simple game of pong, they were able to replicate some of the quirks that are present in human play, which can actually make the player believe that the opponent is intelligent and non-mechanized.

McGlinchey, Stephen (2004). Enabling Computers to Play Games like Humans. In Ercim News 57(1),14 - 16

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