Playing the bluffing game: towards an understanding of deception in games
📜 Abstract
We study the problem of detecting deception in the form of bluffing in games, focussing mainly on card games like poker where bluffing is a key component. We describe a number of algorithms for detecting bluffing and examine their complexity. Finally, we present a detailed example applying one of the algorithms to a simple model of a poker game.
✨ Summary
The paper “Playing the bluffing game: towards an understanding of deception in games” explores the concept of bluffing in games, especially in card games such as poker, where deception is crucial. The authors, Simon Parsons, Carles Sierra, and Sarit Kraus, discuss various algorithms designed to detect bluffing and analyze their complexities. An illustrative example applies one algorithm to a simplified poker model, highlighting its practical implications.
The paper contributes to the field of game theory by providing a foundation for understanding and algorithmically detecting deceptive behavior in games. While specific impact data with concrete academic or industry influence could not be found directly related to this paper, the topics covered are undeniably significant for research in strategic decision-making in artificial intelligence and agent-based systems. These foundational insights likely influence advanced developments in AI bluff detection and opponent modeling in strategic games.