Failing to solve Manic Miner with RL

The author recounts their attempt to use reinforcement learning to solve the classic game Manic Miner, initially facing failures with standard methods. They pivoted to traditional search algorithms, eventually creating a solution that optimized movement without reliance on machine learning, reducing search time significantly. The post highlights lessons learned and the effectiveness of classical algorithmic approaches over contemporary ML techniques in this specific context.