| Simulation-based algorithms for Markov decision processes HS Chang, J Hu, MC Fu, SI Marcus Springer, 2013 | 348 | 2013 |
| An adaptive sampling algorithm for solving Markov decision processes HS Chang, MC Fu, J Hu, SI Marcus Operations Research 53 (1), 126-139, 2005 | 205 | 2005 |
| Multitime scale Markov decision processes HS Chang, PJ Fard, SI Marcus, M Shayman IEEE Transactions on Automatic Control 48 (6), 976-987, 2003 | 110 | 2003 |
| A framework for simulation-based network control via hindsight optimization EKP Chong, RL Givan, HS Chang Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No …, 2000 | 108 | 2000 |
| On-line Scheduling via Sampling. HS Chang, R Givan, EKP Chong AIPS, 62-71, 2000 | 104 | 2000 |
| Parallel rollout for online solution of partially observable Markov decision processes HS Chang, R Givan, EKP Chong Discrete Event Dynamic Systems 14, 309-341, 2004 | 96 | 2004 |
| Converging marriage in honey-bees optimization and application to stochastic dynamic programming HS Chang Journal of Global Optimization 35, 423-441, 2006 | 63 | 2006 |
| Evolutionary policy iteration for solving Markov decision processes HS Chang, HG Lee, MC Fu, SI Marcus IEEE Transactions on Automatic Control 50 (11), 1804-1808, 2005 | 61 | 2005 |
| Google DeepMind's AlphaGo: operations research's unheralded role in the path-breaking achievement. HS Chang, MC Fu, J Hu, SI Marcus Or/Ms Today 43 (5), 24-30, 2016 | 55 | 2016 |
| A stochastic approximation framework for a class of randomized optimization algorithms J Hu, P Hu, HS Chang IEEE Transactions on Automatic Control 57 (1), 165-178, 2011 | 54 | 2011 |
| An asymptotically efficient simulation-based algorithm for finite horizon stochastic dynamic programming HS Chang, MC Fu, J Hu, SI Marcus IEEE Transactions on Automatic Control 52 (1), 89-94, 2007 | 43 | 2007 |
| Approximate receding horizon approach for Markov decision processes: Average reward case HS Chang, SI Marcus Journal of Mathematical Analysis and Applications 286 (2), 636-651, 2003 | 42 | 2003 |
| Two-person zero-sum Markov games: receding horizon approach HS Chang, SI Marcus IEEE transactions on automatic control 48 (11), 1951-1961, 2003 | 40 | 2003 |
| SHAGE: a framework for self-managed robot software D Kim, S Park, Y Jin, H Chang, YS Park, IY Ko, K Lee, J Lee, YC Park, ... Proceedings of the 2006 international workshop on Self-adaptation and self …, 2006 | 38 | 2006 |
| A survey of some simulation-based algorithms for Markov decision processes HS Chang, MC Fu, J Hu, SI Marcus | 31 | 2007 |
| An ant system based exploration-exploitation for reinforcement learning HS Chang 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat …, 2004 | 30 | 2004 |
| Adaptive adversarial multi-armed bandit approach to two-person zero-sum Markov games HS Chang, J Hu, MC Fu, SI Marcus IEEE transactions on automatic control 55 (2), 463-468, 2010 | 25 | 2010 |
| Reinforcement learning with supervision by combining multiple learnings and expert advices HS Chang 2006 American Control Conference, 6 pp., 2006 | 22 | 2006 |
| Recursive learning automata approach to Markov decision processes HS Chang, MC Fu, J Hu, SI Marcus IEEE Transactions on Automatic Control 52 (7), 1349-1355, 2007 | 21 | 2007 |
| A policy improvement method in constrained stochastic dynamic programming HS Chang IEEE transactions on automatic control 51 (9), 1523-1526, 2006 | 20 | 2006 |
