This post discusses an innovative version of the classic game Rock, Paper, Scissors that utilizes Markov chains to adapt and learn from the player's strategy over time. Players have noted varying degrees of success and challenges in trying to outsmart the learning mechanism, suggesting that it creates an interesting dynamic. Comments highlight both the fun aspect of the game and the frustration that arises from its learning capabilities. Users attempted strategies rooted in psychology and pattern recognition, showing a blend of creativity and analytical thinking. The feedback includes reflections on the game's humorous graphics and sound design, emphasizing its entertaining elements while also noting its limitations in longevity. There is also a reference to Claude Shannon's work on game theory and prediction.