Conference Papers
  1. H. S. Chang, R. L. Givan, and E. K. P. Chong, On-line Scheduling via Sampling,
    in Proc. of the 5th Int. Conf. on Artificial Intelligence Planning and Scheduling, 2000, pp. 62-71.
  2. E. K. P. Chong, R. L. Givan, and H. S. Chang, A Framework for Simulation-based Network Control via Hindsight Optimization,
    in Proc. of the 39th IEEE Conf. on Decision and Control, Vol. 2, 2000, pp. 1433-1438.
  3. H. S. Chang, P. Fard, S. I. Marcus, and M. Shayman, A Model for Multi-time Scaled Sequential Decision Making Processes,
    in Proc. of the 41st IEEE Conf. on Decision and Control, Vol. 4, 2002, pp. 3813-3818.
  4. H. S. Chang and S. I. Marcus, Receding Horizon Approach to Markov Games for Infinite Horizon Discounted Cost,
    in Proc. of the 41st IEEE Conf. on Decision and Control, Vol. 2, 2002, pp. 1380-1385.
  5. K. Kuo, S. Phuvoravan, R. La, S. Bhattacharjee, M. Shayman, and H. S. Chang, On the use of flow migration for handling short-term overloads,
    in Proc. of the IEEE Globecom, Vol. 6, 2003, pp. 3108-3112.
  6. H. S. Chang and M. Fu, A Distributed Algorithm for Solving a Class of Multi-agent Markov Decision Problems,
    in Proc. of the 42nd IEEE Conf. on Decision and Control, Vol. 5, 2003, pp. 5341-5346.
  7. H. S. Chang, M. Fu, and S. I. Marcus, An Asymptotically Efficient Algorithm for Solving Finite Horizon Stochastic Dynamic Programming Problems,
    in Proc. of the 42nd IEEE Conf. on Decision and Control, Vol. 4, 2003, pp. 3818-3823.
  8. S. W. Kim and H. S. Chang, Parallelizing parallel rollout algorithm for solving Markov decision processes,
    Lecture Notes in Computer Science, Springer-Verlag, Vol. 2176, pp. 122-136, 2003.
  9. H. S. Chang, W. J. Gutjahr, J. Yang, and S. Park, An Ant System Approach to Markov Decision Processes,
    in Proc. of the 23rd American Control Conference, Vol. 4, 2004, pp. 3820-3825.
  10. H. S. Chang, On the Use of Blackwell's Approachability Theorem for Stochastic Dynamic Programming,
    in Proc. of the IFAC Workshop on Adaptation and Learning in Control and Signal Processing (ALCOSP 04), 2004, pp. 765-770.
  11. H. S. Chang, An Ant System Based Exploration-Exploitation for Reinforcement Learning,
    in Proc. of the IEEE Conf. on Systems, Man, and Cybernetics, Vol. 4, 2004, pp. 3805-3810.
  12. H. S. Chang, An Adaptation of Particle Swarm Optimization for Markov Decision Processes,
    in Proc. of the IEEE Conf. on Systems, Man, and Cybernetics, Vol. 2, 2004, pp. 1643-1648.
  13. H. S. Chang and M. Fu, Localization for a Class of Two-Team Zero-Sum Markov Games,
    in Proc. of the 43rd IEEE Conf. on Decision and Control, Vol. 5, 2004, pp. 4844-4849.
  14. S-Y. Lee and H. S. Chang, An Ant System Based Multicasting in Mobile Ad Hoc Network,
    in Proc. of the IEEE Congress on Evolutionary Computation, Vol. 2, 2005, pp. 1583-1588.
  15. H. S. Chang, M. Fu, and S. I. Marcus, Recursive Learning Automata for Control of Partially Observable Markov Decision Processes,
    in Proc. of the Joint 44th IEEE Conf. on Decision and Control and European Control Conf., 2005, pp. 6091-6096.
  16. H. S. Chang and E. K. P. Chong, On Solving Controlled Markov Set-Chains via Multi-Policy Improvement,
    in Proc. of the Joint 44th IEEE Conf. on Decision and Control and European Control Conf., 2005, pp. 8058-8063.
  17. S-Y. Lee and H. S. Chang, Durable Distance Vector Multicasting Protocol for Mobile Ad Hoc Networks,
    in Proc. of the IEEE Conf. on Networking, Sensing, and Control, 2006, pp. 6-11.
  18. H. S. Chang, Reinforcement Learning with Supervision by Combining Multiple Learnings and Expert Advices,
    in Proc. of the 25th American Control Conference, 2006, pp. 4159-4164.
  19. H. S. Chang, On Policy Iteration for Finite Horizon Markov Decision Processes with Target-Level Risk Sensitive Objectives,
    in Proc. of the 17th Int. Symposium on Mathematical Theory of Networks and Systems, 2006, pp. 1256-1258.
  20. H. S. Chang, On Combining Multiple Heuristic Policies in Minimax Control,
    in Proc. of the 17th Int. Symposium on Mathematical Theory of Networks and Systems, 2006, pp. 2738-2741.
  21. D. Kim, S. Park, Y. Jin, H. S. Chang, Y. Park, I. Ko, K. Lee, J. Lee, Y. Park, and S. Lee, SHAGE: A Framework for Self-Managed Robot Software,
    in Proc. of the Int. Workshop on Self-Adaptation and Self-Managing systems, 2006, pp. 79-85.
  22. H. S. Chang, M. Fu, and S. I. Marcus, Adversarial Multi-Armed Bandit Approach to Stochastic Optimization,
    in Proc. of the 45th IEEE Conf. on Decision and Control, 2006, pp. 5681-5686.
  23. H. S. Chang, M. Fu, and S. I. Marcus, Adversarial Multi-Armed Bandit Approach to Two-Person Zero-Sum Markov Games,
    in Proc. of the 46th IEEE Conf. on Decision and Control, 2007, pp. 127-132.
  24. H. S. Chang, Stochastic Iterative Approximation for Parallel Rollout and Policy Switching,
    in Proc. of the 17th Int. Federation of Automatic Control (IFAC) World Congress, 2008, pp. 15475-15479.
  25. J. Hu and H. S. Chang, A Population-Based Cross-Entropy Method with Dynamic Sample Allocation,
    in Proc. of the 47th IEEE Conf. on Decision and Control, 2008, pp. 2426-2431.
  26. J. Hu and H. S. Chang, An Approximate Stochastic Annealing Algorithm for Finite Horizon Markov Decision Processes,
    in Proc. of the 49th IEEE Conf. on Decision and Control, 2010, pp. 5338-5343.
Misc.