Program Synthesis Guided Reinforcement Learning for Partially Observed
Environments

Program Synthesis Guided Reinforcement Learning for Partially Observed Environments

22 February 2021

Armando Solar-Lezama

Papers citing "Program Synthesis Guided Reinforcement Learning for Partially Observed Environments"

10 / 10 papers shown

Title
Improving Reliable Navigation under Uncertainty via Predictions Informed by Non-Local Information Raihan Islam Arnob Gregory J. Stein 30 2 0 26 Jul 2023
TASKOGRAPHY: Evaluating robot task planning over large 3D scene graphs Christopher Agia Krishna Murthy Jatavallabhula M. Khodeir O. Mikšík Vibhav Vineet Mustafa Mukadam Liam Paull Florian Shkurti 22 67 0 11 Jul 2022
A Hierarchical Bayesian Approach to Inverse Reinforcement Learning with Symbolic Reward Machines Weichao Zhou Wenchao Li BDL 20 11 0 20 Apr 2022
Exploring with Sticky Mittens: Reinforcement Learning with Expert Interventions via Option Templates Souradeep Dutta Kaustubh Sridhar Osbert Bastani Edgar Dobriban James Weimer Insup Lee J. Parish-Morris 17 2 0 25 Feb 2022
Programmatic Reward Design by Example Weichao Zhou Wenchao Li 32 15 0 14 Dec 2021
Learning Language-Conditioned Robot Behavior from Offline Data and Crowd-Sourced Annotation Suraj Nair E. Mitchell Kevin Chen Brian Ichter Silvio Savarese Chelsea Finn LM&Ro OffRL 23 154 0 02 Sep 2021
Learning to Synthesize Programs as Interpretable and Generalizable Policies Dweep Trivedi Jesse Zhang Shao-Hua Sun Joseph J. Lim NAI 9 71 0 31 Aug 2021
Hierarchical Reinforcement Learning By Discovering Intrinsic Options Jesse Zhang Haonan Yu W. Xu BDL 125 82 0 16 Jan 2021
Learning Differentiable Programs with Admissible Neural Heuristics Ameesh Shah Eric Zhan Jennifer J. Sun Abhinav Verma Yisong Yue Swarat Chaudhuri 131 43 0 23 Jul 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 311 11,681 0 09 Mar 2017