Acknowledgements This paper was supported by the National Natural Science Foundation of China (Grant Nos. 61272005, 61070223, 61103045, 60970015, and 61170020), Natural Science Foundation of Jiangsu (BK2012616, BK2009116), High School Natural Foundation of Jiangsu (09KJA520002), and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University (93K172012K04).
The main challenge in the area of reinforcement learning is scaling up to larger and more complex problems. Aiming at the scaling problem of reinforcement learning, a scalable reinforcement learning method, DCS-SRL, i...