Deceptive Games
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Abstract (arXiv)
Deceptive games are games where the reward structure or other aspects of the game are designed to lead the agent away from a globally optimal policy. While many games are already deceptive to some extent, we designed a series of games in the Video Game Description Language (VGDL) implementing specific types of deception, classified by the cognitive biases they exploit. VGDL games can be run in the General Video Game Artificial Intelligence (GVGAI) Framework, making it possible to test a variety of existing AI agents that have been submitted to the GVGAI Competition on these deceptive games. Our results show that all tested agents are vulnerable to several kinds of deception, but that different agents have different weaknesses. This suggests that we can use deception to understand the capabilities of a game-playing algorithm, and game-playing algorithms to characterize the deception displayed by a game.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 31 Jan 2018.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 0; 2024: 1.
5 papers.
- 2022Generative Personas That Behave and Experience Like Humanscited by 7
- 2022Play with Emotion: Affect-Driven Reinforcement Learningcited by 6
- 2021Deceptive Level Generation for Angry Birdscited by 5
- 2021Game Mechanic Alignment Theory and Discoverycited by 1
- 2024PyTAG: Tabletop Games for Multi-Agent Reinforcement Learningcited by 1
- 2024PyTAG: Tabletop Games for Multi-Agent Reinforcement Learning28 May 2024
- 2022Generative Personas That Behave and Experience Like Humans26 Aug 2022
- 2022Play with Emotion: Affect-Driven Reinforcement Learning26 Aug 2022
- 2021Deceptive Level Generation for Angry Birds3 Jun 2021
- 2021Game Mechanic Alignment Theory and Discovery20 Feb 2021