Reinforcement Learning for Processing Networks seminar

Previous presentations:

Title: Algorithms for exploration in reinforcement learning

Discussion leaders: Xiuyuan (Lucy) Lu

Date: 08/06/2018

References:

• Jaksch, Ortner, Auer (2010). “Near-optimal Regret Bounds for Reinforcement Learning”. Journal of Machine Learning Research 11, pp 1563-1600. Link
• Osband, Russo, Van Roy (2013). "(More) Efficient Reinforcement Learning via Posterior Sampling". Link
• Osband, Van Roy (2017) "Why is Posterior Sampling Better than Optimism for Reinforcement Learning?" Proceedings of the 34th International Conference on Machine Learning. Link
• Osband, Van Roy, Russo, Wen (2018) "Deep Exploration via Randomized Value Functions". Link

Title: An Information-Theoreric Analysis of Thompson Sampling

Discussion leaders: Xiuyuan (Lucy) Lu and Vikranth Dwaracherla

Date: 07/23/2018

References:

• Russo, D. and B. Van Roy. 2016. “An Information-Theoretic analysis of Thompson sampling”. Journal of Machine Learning Research. 17(68): 1–30. Link

Title: Inpatient Overflow: An Approximate Dynamic Programming Approach

Discussion leader: Pengyi Shi

Date: 07/16/2018

References:

• J. Dai, P. Shi, Inpatient Overflow: An Approximate Dynamic Programming Approach (February 20, 2018). Forthcoming, Manufacturing and Service Operations Management (MSOM). Link

Title: A Finite Time Analysis of TD Learning using with Linear Function Approximation

Discussion leader: Mark Gluzman

Date: 07/09/2018

References:

• J. Bhandari, D.Russo, R. Singal (2018) A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation, https://arxiv.org/abs/1806.02450 Link