Solving Compositional Reinforcement Learning Problems via Task Reduction

13 March 2021

Papers citing "Solving Compositional Reinforcement Learning Problems via Task Reduction"

9 / 9 papers shown

Title
Reduce, Reuse, Recycle: Categories for Compositional Reinforcement Learning Georgios Bakirtzis M. Savvas Ruihan Zhao Sandeep P. Chinchali Ufuk Topcu 40 2 0 23 Aug 2024
MeMo: Meaningful, Modular Controllers via Noise Injection Megan Tjandrasuwita Jie Xu Armando Solar-Lezama Wojciech Matusik 21 0 0 24 May 2024
Towards Zero-Shot Functional Compositionality of Language Models Hangyeol Yu Myeongho Jeong Jamin Shin Hyeongdon Moon Juneyoung Park Seungtaek Choi 37 1 0 06 Mar 2023
E-MAPP: Efficient Multi-Agent Reinforcement Learning with Parallel Program Guidance C. Chang Ni Mu Jiajun Wu Ling Pan Huazhe Xu 50 7 0 05 Dec 2022
Categorical semantics of compositional reinforcement learning Georgios Bakirtzis M. Savvas Ufuk Topcu CoGe 40 4 0 29 Aug 2022
How to Reuse and Compose Knowledge for a Lifetime of Tasks: A Survey on Continual Learning and Functional Composition Jorge Armando Mendez Mendez Eric Eaton KELM CLL 32 27 0 15 Jul 2022
Phasic Self-Imitative Reduction for Sparse-Reward Goal-Conditioned Reinforcement Learning Yunfei Li Tian Gao Jiaqi Yang Huazhe Xu Yi Wu OffRL 19 22 0 24 Jun 2022
Environment Generation for Zero-Shot Compositional Reinforcement Learning Izzeddin Gur Natasha Jaques Yingjie Miao Jongwook Choi Manoj Kumar Tiwari Honglak Lee Aleksandra Faust 36 43 0 21 Jan 2022
Multi-Task Learning with Sequence-Conditioned Transporter Networks M. H. Lim Andy Zeng Brian Ichter Maryam Bandari Erwin Coumans Claire Tomlin S. Schaal Aleksandra Faust 37 14 0 15 Sep 2021