Filters








4 Hits in 1.6 sec

DualSMC: Tunneling Differentiable Filtering and Planning under Continuous POMDPs [article]

Yunbo Wang, Bo Liu, Jiajun Wu, Yuke Zhu, Simon S. Du, Li Fei-Fei, Joshua B. Tenenbaum
2020 arXiv   pre-print
We cast POMDP filtering and planning problems as two closely related Sequential Monte Carlo (SMC) processes, one over the real states and the other over the future optimal trajectories, and combine the  ...  Based on the filtering results, we then propose a planning algorithm that extends the previous SMC planning approach [Piche et al., 2018] to continuous POMDPs with an uncertainty-dependent policy.  ...  Our contributions to continuous POMDPs with DualSMC can be summarized as follows: • It proposes a new differentiable particle filter (DPF) that leverages the adversarial relationship between the internals  ... 
arXiv:1909.13003v4 fatcat:4xbmv22ccjcxfe6hltkpzrmv3y

DualSMC: Tunneling Differentiable Filtering and Planning under Continuous POMDPs

Yunbo Wang, Bo Liu, Jiajun Wu, Yuke Zhu, Simon S. Du, Li Fei-Fei, Joshua B. Tenenbaum
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
We cast POMDP filtering and planning problems as two closely related Sequential Monte Carlo (SMC) processes, one over the real states and the other over the future optimal trajectories, and combine the  ...  Based on the filtering results, we then propose a planning algorithm that extends the previous SMC planning approach [Piche et al., 2018] to continuous POMDPs with an uncertainty-dependent policy.  ...  Acknowledgements The Center for Information and Bubble Studies is funded by the Carlsberg Foundation. RKR was partially supported by the DFG-ANR joint project Collective Attitude Formation .  ... 
doi:10.24963/ijcai.2020/575 dblp:conf/ijcai/LibermanR20 fatcat:mxm7bcjddbfknodhwwchmpbmtu

Visual Learning-based Planning for Continuous High-Dimensional POMDPs [article]

Sampada Deglurkar, Michael H. Lim, Johnathan Tucker, Zachary N. Sunberg, Aleksandra Faust, Claire J. Tomlin
2021 arXiv   pre-print
In this work, we propose Visual Tree Search (VTS), a learning and planning procedure that combines generative models learned offline with online model-based POMDP planning.  ...  The Partially Observable Markov Decision Process (POMDP) is a powerful framework for capturing decision-making problems that involve state and transition uncertainty.  ...  entiable Filtering and Planning under Continuous POMDPs. Kochenderfer, M. J. 2015. Decision Making Under Uncer- In Bessiere, C., ed., IJCAI, 4190–4198.  ... 
arXiv:2112.09456v1 fatcat:xhx4ogcejbg6zlixpjue3jowzm

Structured World Belief for Reinforcement Learning in POMDP [article]

Gautam Singh, Skand Peri, Junghyun Kim, Hyunseok Kim, Sungjin Ahn
2021 arXiv   pre-print
In experiments, we show that object-centric belief provides a more accurate and robust performance for filtering and generation.  ...  Object-centric world models provide structured representation of the scene and can be an important backbone in reinforcement learning and planning.  ...  by autonomous connecting, controlling and evolving ways].  ... 
arXiv:2107.08577v1 fatcat:7s7pwcmfubbzzk23dagdttcocy