Reinforcement Strategy Using Quantum Amplitude Amplification for Robot Learning

摘要

Quantum amplitude amplification is a kind of useful technique in quantum computation and it can boost the success probability of some quantum algorithms. Reinforcement strategy in reinforcement learning is essentially to boost the selection probability of "good" action. Considering the common characteristics, this paper uses the idea of amplitude amplification to reinforcement learning as a new reinforcement strategy, proposes a learning algorithm based on quantum amplitude amplification and demonstrates its effectiveness through simulated experiments.