Action Recognition for Support of Adaptive Gameplay: A Case Study of a First Person Shooter

Abstract

With games continuously and rapidly evolving to become more complex and sophisticated in their nature and implementation. There is a fundamental need to sustain and deliver a similarly advanced, realistic, and engaging experience for the player. The implementation of “emergence” within games as providing an effective means to sustain this engagement in conjunction with some form of action recognition mechanism for its support. More recently, games have made much of the “adaptive” mechanisms that tailor the player experience during the game, but much of this appears to be implemented by merely making the game harder according to the success of the player. Some go further than this by incorporating adaptive AI that change agent tactics to suit the player's style of play. Whilst these are clearly advances in the approach to providing a player-centric experience to engage the player, the basis and transferability of these approaches is open to question. Here we propose a limited flavour of “emergence” which can be used to support an adaptive game mechanism and so present players with different gameplay experiences based on their actions within the game.