AI as Evaluator: Search Driven Playtesting of Modern Board Games
Silva, Fernando De Mesentier (New York University) | Lee, Scott (New York University) | Togelius, Julian (New York University) | Nealen, Andy (New York University)
This paper presents a demonstration of how AI can be useful in the game design and development process of a modern board game. By using an artificial intelligence algorithm to play a substantial amount of matches of the Ticket to Ride board game and collecting data, we can analyze several features of the gameplay as well as of the game board. Results revealed loopholes in the game's rules and pointed towards trends in how the game is played. We are then led to the conclusion that large scale simulation utilizing artificial intelligence can offer valuable information regarding modern board games and their designs that would ordinarily be prohibitively expensive or time-consuming to discover manually.
Feb-4-2017
- Country:
- Asia > India (0.05)
- South America > Brazil (0.04)
- Oceania > Australia
- Queensland (0.04)
- North America
- United States
- New York > Kings County
- New York City (0.04)
- Nevada > Clark County
- Las Vegas (0.04)
- New York > Kings County
- Canada > Ontario
- Toronto (0.04)
- United States
- Europe
- Switzerland > Zürich
- Zürich (0.04)
- Netherlands > Limburg
- Maastricht (0.04)
- Switzerland > Zürich
- Genre:
- Research Report (0.46)
- Industry:
- Leisure & Entertainment > Games > Computer Games (1.00)
- Technology: