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Abstract and slides for a Directed Study research survey paper regarding implementation strategies for collaborative AI characters in games.

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AI Research for Collaborative Game Characters

Study materials for a research survey paper in collaboration in AI characters for games. Abstract and works cited here.

Description

As part of my masters' studies and research, I created a survey paper focusing on the subject of building better collaborative AI characters in games. Collaborative AI is defined as one or more non-player characters (agents) crafted to interact and work with the Player and/or other agents.

The survey covered five challenging tasks for AI design and implementation:

Movement: Strategies for having AI characters move in collaboration with steering behaviours and pathfinding techniques.

Knowledge Communication: Strategies for having AI-controlled characters share and communicate local knowledge about themselves and the environment.

Decision-Making: Strategies for collaborative decision-making between characters in pursuit of common goals including tactical and strategic behaviour.

Learning: Strategies for having AI characters learn together to solve tasks more efficiently.

Player Interaction: Strategies for facilitating better communication between AI characters and the Player.

Scope

The scope of the research is encompassed in this diagram: Tree-like chart of AI techniques covered

The brief abstract included in this repository also has the full list of works cited.

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Abstract and slides for a Directed Study research survey paper regarding implementation strategies for collaborative AI characters in games.

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