Energy efficiency is critical for the locomotion of quadruped robots. However, energy values found in simulations do not transfer adequately to real world. To address this issue, we present a novel method, named Policy Search Transfer Optimization (PSTO), which combines deep reinforcement learning and optimization create energy-efficient robots The policy search process are performed by TD3 alg...