【论文整理】model-based control Model Learning and Model-predictive Control (MPC)

Model Learning and Model-predictive Control (MPC)

• Learning model-based planning from scratch, R. Pascanu and Y.Li et al., Arxiv 2017
• Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models, K. Chua et al., NIPS 2018
• SOLAR: Deep Structured Latent Representations for Model-Based Reinforcement Learning, M. Zhang et al., arXiv 2018
• Interaction Networks for Learning about Objects, Relations and Physics, P. Battaglia et al., NIPS 2016 ⭐️
• Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids, Y. Li et al., arXiv 2018 ⭐️
• Propagation Networks for Model-Based Control Under Partial Observation, Y. Li et al., arXiv 2018
• Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation, D. Corneil et al., ICML 2018 ⭐️
• A Compositional Object-Based Approach to Learning Physical Dynamics, M. Chang et al., ICLR 2017 ⭐️
• SPNets: Differentiable Fluid Dynamics for Deep Neural Networks, C. Schenck et al., CoRL 2018
• Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncing, A. Ajay et al., IROS 2018
• Graph networks as learnable physics engines for inference and control, A. Sanchez-Gonzalez et al., arXiv 2018 ⭐️
• Learning Latent Dynamics for Planning from Pixels, D. Hafner et al., arXiv 2018