Learning to Synthesize Programs as Interpretable and Generalizable Policies

31 August 2021

Papers citing "Learning to Synthesize Programs as Interpretable and Generalizable Policies"

45 / 45 papers shown

Title
Beyond Predefined Actions: Integrating Behavior Trees and Dynamic Movement Primitives for Robot Learning from Demonstration David Cáceres-Domínguez Erik Schaffernicht Todor Stoyanov 24 0 0 13 May 2025
Learning local discrete features in explainable-by-design convolutional neural networks Pantelis I. Kaplanoglou Konstantinos Diamantaras FAtt 51 1 0 31 Oct 2024
Human-Readable Programs as Actors of Reinforcement Learning Agents Using Critic-Moderated Evolution Senne Deproost Denis Steckelmacher Ann Nowé 36 0 0 29 Oct 2024
Reclaiming the Source of Programmatic Policies: Programmatic versus Latent Spaces Tales H. Carvalho Kenneth Tjhia Levi H. S. Lelis 36 6 0 16 Oct 2024
KnowPC: Knowledge-Driven Programmatic Reinforcement Learning for Zero-shot Coordination Yin Gu Qi Liu Zhi Li Kai Zhang 31 0 0 08 Aug 2024
Unveiling the Decision-Making Process in Reinforcement Learning with Genetic Programming Manuel Eberhardinger Florian Rupp Johannes Maucher S. Maghsudi 30 0 0 20 Jul 2024
Language Models can Infer Action Semantics for Classical Planners from Environment Feedback Wang Zhu Ishika Singh Robin Jia Jesse Thomason LM&Ro ReLM LRM 53 0 0 04 Jun 2024
Synthesizing Programmatic Reinforcement Learning Policies with Large Language Model Guided Search Max Liu Chan-Hung Yu Wei-Hsu Lee Cheng-Wei Hung Yen-Chun Chen Shao-Hua Sun 55 4 0 26 May 2024
Generating Code World Models with Large Language Models Guided by Monte Carlo Tree Search Nicola Dainese Matteo Merler Minttu Alakuijala Pekka Marttinen LLMAG 41 8 0 24 May 2024
Searching for Programmatic Policies in Semantic Spaces Rubens O. Moraes Levi H. S. Lelis 30 4 0 08 May 2024
What Foundation Models can Bring for Robot Learning in Manipulation : A Survey Dingzhe Li Yixiang Jin A. Yong Hongze Yu Jun Shi Xiaoshuai Hao Peng Hao Huaping Liu Gang Hua Bin Fang AI4CE LM&Ro 72 13 0 28 Apr 2024
Mechanistic Interpretability for AI Safety -- A Review Leonard Bereska E. Gavves AI4CE 40 114 0 22 Apr 2024
TwoStep: Multi-agent Task Planning using Classical Planners and Large Language Models Ishika Singh David Traum Jesse Thomason Jesse Thomason LM&Ro LLMAG 40 16 0 25 Mar 2024
NARRATE: Versatile Language Architecture for Optimal Control in Robotics Seif Ismail Antonio Arbues Ryan Cotterell René Zurbrügg Carmen Amo Alonso LM&Ro 29 4 0 16 Mar 2024
RL-GPT: Integrating Reinforcement Learning and Code-as-policy Shaoteng Liu Haoqi Yuan Minda Hu Yanwei Li Yukang Chen Shu Liu Zongqing Lu Jiaya Jia LLMAG 48 14 0 29 Feb 2024
Pix2Code: Learning to Compose Neural Visual Concepts as Programs Antonia Wüst Wolfgang Stammer Quentin Delfosse Devendra Singh Dhami Kristian Kersting 49 13 0 13 Feb 2024
Three Pathways to Neurosymbolic Reinforcement Learning with Interpretable Model and Policy Networks Peter Graf Patrick Emami 26 2 0 07 Feb 2024
Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents Quentin Delfosse Sebastian Sztwiertnia M. Rothermel Wolfgang Stammer Kristian Kersting 52 18 0 11 Jan 2024
A Survey on Verification and Validation, Testing and Evaluations of Neurosymbolic Artificial Intelligence Justus Renkhoff Ke-ke Feng Marc Meier-Doernberg Alvaro Velasquez Houbing Herbert Song 34 8 0 06 Jan 2024
Enhancing Robot Program Synthesis Through Environmental Context Tianyi Chen Qidi Wang Zhen Dong Liwei Shen Xin Peng 20 4 0 13 Dec 2023
Program Machine Policy: Addressing Long-Horizon Tasks by Integrating Program Synthesis and State Machines Yu-An Lin Chen-Tao Lee Guanhui. Liu Pu-Jen Cheng Shao-Hua Sun 27 0 0 27 Nov 2023
Efficient Symbolic Policy Learning with Differentiable Symbolic Expression Jiaming Guo Rui Zhang Shaohui Peng Qi Yi Xingui Hu ... Zidong Du Xishan Zhang Ling Li Qi Guo Yunji Chen OffRL 22 5 0 02 Nov 2023
Learning a Hierarchical Planner from Humans in Multiple Generations Leonardo Hernandez Cano Yewen Pu Robert D. Hawkins Josh Tenenbaum Armando Solar-Lezama 21 2 0 17 Oct 2023
Bootstrap Your Own Skills: Learning to Solve New Tasks with Large Language Model Guidance Jesse Zhang Jiahui Zhang Karl Pertsch Ziyi Liu Xiang Ren Minsuk Chang Shao-Hua Sun Joseph J. Lim LLMAG LM&Ro 99 60 0 16 Oct 2023
Optimizing Large Language Models to Expedite the Development of Smart Contracts Nii Osae Osae Dade Margaret Lartey-Quaye Emmanuel Teye-Kofi Odonkor Paul Ammah 27 4 0 08 Oct 2023
Learning of Generalizable and Interpretable Knowledge in Grid-Based Reinforcement Learning Environments Manuel Eberhardinger Johannes Maucher S. Maghsudi 29 4 0 07 Sep 2023
Neurosymbolic Reinforcement Learning and Planning: A Survey Kamal Acharya Waleed Raza Carlos Dourado Alvaro Velasquez Houbing Song NAI OffRL 32 16 0 02 Sep 2023
Worrisome Properties of Neural Network Controllers and Their Symbolic Representations J. Cyranka Kevin E. M. Church J. Lessard 39 0 0 28 Jul 2023
A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis Izzeddin Gur Hiroki Furuta Austin Huang Mustafa Safdari Yutaka Matsuo Douglas Eck Aleksandra Faust LM&Ro LLMAG 39 198 0 24 Jul 2023
Pushing the Limits of Machine Design: Automated CPU Design with AI Shuyao Cheng Pengwei Jin Qi Guo Zidong Du Rui Zhang ... Xishan Zhang Yuejie Chu W. Mao Tianshi Chen Yunji Chen 43 5 0 21 Jun 2023
Language to Rewards for Robotic Skill Synthesis Wenhao Yu Nimrod Gileadi Chuyuan Fu Sean Kirmani Kuang-Huei Lee ... N. Heess Dorsa Sadigh Jie Tan Yuval Tassa F. Xia LM&Ro 37 269 0 14 Jun 2023
Adaptive and Explainable Deployment of Navigation Skills via Hierarchical Deep Reinforcement Learning Kyowoon Lee Seongun Kim Jaesik Choi 21 9 0 31 May 2023
Reinforcement Learning with Knowledge Representation and Reasoning: A Brief Survey Chao Yu Xuejing Zheng H. Zhuo OffRL LRM 55 7 0 24 Apr 2023
Embodied Concept Learner: Self-supervised Learning of Concepts and Mapping through Instruction Following Mingyu Ding Yan Xu Zhenfang Chen David D. Cox Ping Luo J. Tenenbaum Chuang Gan LM&Ro 56 21 0 07 Apr 2023
Hierarchical Neural Program Synthesis Linghan Zhong Ryan Lindeborg Jesse Zhang Joseph J. Lim Shao-Hua Sun 24 9 0 09 Mar 2023
Programmatic Imitation Learning from Unlabeled and Noisy Demonstrations Jimmy Xin Linus Zheng Kia Rahmani Jiayi Wei Jarrett Holtz Işıl Dillig Joydeep Biswas 30 1 0 02 Mar 2023
Hierarchical Programmatic Reinforcement Learning via Learning to Compose Programs Guanhui. Liu En-Pei Hu Pu-Jen Cheng Hung-yi Lee Shao-Hua Sun 69 17 0 30 Jan 2023
A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, Challenges Yunpeng Qing Shunyu Liu Jie Song Huiqiong Wang Mingli Song XAI 30 1 0 12 Nov 2022
CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning Hung Le Yue Wang Akhilesh Deepak Gotmare Silvio Savarese S. Hoi SyDa ALM 129 240 0 05 Jul 2022
From {Solution Synthesis} to {Student Attempt Synthesis} for Block-Based Visual Programming Tasks Adish Singla Nikitas Theodoropoulos 25 13 0 03 May 2022
Iterative Genetic Improvement: Scaling Stochastic Program Synthesis Yuan Yuan W. Banzhaf 20 4 0 26 Feb 2022
Competition-Level Code Generation with AlphaCode Yujia Li David Choi Junyoung Chung Nate Kushman Julian Schrittwieser ... Esme Sutherland Robson Pushmeet Kohli Nando de Koray Kavukcuoglu Oriol Vinyals 26 1,299 0 08 Feb 2022
ProTo: Program-Guided Transformer for Program-Guided Tasks Zelin Zhao Karan Samel Binghong Chen Le Song ViT LM&Ro 29 30 0 02 Oct 2021
Unsupervised Learning of Neurosymbolic Encoders Eric Zhan Jennifer J. Sun Ann Kennedy Yisong Yue Swarat Chaudhuri 16 13 0 28 Jul 2021
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 338 11,684 0 09 Mar 2017