An Autonomic Chess Bot Detection & Defeat System

Due to the rise of online chess, the increasing dominance of automated chess bots, and high-profile cheating allegations in chess recently, there has been a growing interest in applying bot detection for chess. The existing methods in this field primarily rely on player history, anomaly detection, and engine analysis to attempt to identify engine play after it has occurred. These post-facto analysis methods generalize poorly to real-time autonomy detection domains such as real-time cybersecurity. This paper suggests a new challenge in which bot detection must be done on an opposing player mid-game, allowing for a dynamic strategy based on the identification made of the opponent. This paper then suggest an autonomic system which could use the self-chop properties in order to meet this challenge.