Buyout! is a 4-player table-top game about the business giant Megacorp deciding to sell-up and liquidate its shares. Players take the role of 1 of 4 businessmen looking to buyout as many of the remaining shares as possible so they can take over and repurpose Megacorps facilities for their own use.

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The board game was designed and created during my first year of my BA (Honours) in Games Design. The key focus of this project as a designer was to sell the narrative that the players were businessmen. To do that, I made sure that as many pieces of the project reflected that aesthetic back to the players during play:

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• The box itself is a leather briefcase

• To trade resources, player swap miniature briefcases

• Whomever is currently in the lead wears the tie

• The rules are stored in a secretive corporate looking holder

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In my final year of university, for my Honours project, I looked at translating the boardgame into a videogame using Unreal Engine 4 as a means to test my technical designer capabilities. Due to the limitations of the course itself I would not be able to make this an online-based multiplayer game, and due to a core mechanic of the game being deception, local multiplayer was off the table too. This means that I had to create a single player version of the game with AI to replicate the other three players needed to play.

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During the creation process, the AI acted randomly, and it was obvious the AI wasn’t really ‘thinking’ about what it was doing. This was highlighted to me in feedback I received from my tutors. To remedy this issue, I researched cognitive psychology and human decision making and re-created the AI in line with Eysenck & Keanes 'Theory of Naturalistic Decision-Making' (2015) to make the decisions they made more human. This created an AI that would…

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• Set their own goals based off its own wants and needs.

• Gather information from the responses it receives from the other players.

• Structure their decision by weighing up the value of all offers presented to it.

• Make a final choice based off what the most valuable offer presented is, and if the player offering that proposal can be trusted.

• Evaluate the decision based off if it was lied to by its trade partner. The AI will remember this.

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Leading to a much more engaging, and difficult, gameplay experience.​