Deceptive Games

TL;DR

This paper introduces a series of deceptive video games designed to exploit cognitive biases, testing AI agents' vulnerabilities and providing insights into their capabilities and weaknesses.

Contribution

It presents a novel set of deceptive games in VGDL, enabling analysis of AI agents' susceptibility to deception and advancing understanding of game-playing AI behavior.

Findings

All tested agents are vulnerable to deception.

Different agents exhibit different weaknesses.

Deception can be used to characterize AI capabilities.

Abstract

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.