Timezone: »
Systematic compositionality - the ability to combine learned knowledge and skills to solve novel tasks -- is a key aspect of generalization in humans that allows us to understand and perform tasks described by novel language utterances. While progress has been made in supervised learning settings, no work has yet studied compositional generalization of a reinforcement learning agent following natural language instructions in an embodied environment. We develop a set of tasks in a photo-realistic simulated kitchen environment that allow us to study the degree to which a behavioral policy captures the systematicity in language by studying its zero-shot generalization performance on held out natural language instructions. We show that our agent which leverages a novel additive action-value decomposition in tandem with attention-based subgoal prediction is able to exploit composition in text instructions to generalize to unseen tasks.
Author Information
Lajanugen Logeswaran (University of Michigan)
Wilka Carvalho (University of Michigan)
I am a Masters student and NSF Graduate Research Fellow in the Computer Science Department at the University of Southern California. My primary research interest is the development of neuroscience- and cognitive science-informed artificial intelligence and machine learning models with brain-rivaling information-processing capabilities.
Honglak Lee (U. Michigan)
More from the Same Authors
-
2020 : Few-shot Sequence Learning with Transformers »
Lajanugen Logeswaran -
2021 : Learning Action Translator for Meta Reinforcement Learning on Sparse-Reward Tasks »
Yijie Guo · Qiucheng Wu · Honglak Lee -
2021 : Fast Inference and Transfer of Compositional Task for Few-shot Task Generalization »
Sungryull Sohn · Hyunjae Woo · Jongwook Choi · Izzeddin Gur · Aleksandra Faust · Honglak Lee -
2021 : Learning Parameterized Task Structure for Generalization to Unseen Entities »
Anthony Liu · Sungryull Sohn · Honglak Lee -
2021 : Task-driven Discovery of Perceptual Schemas for Generalization in Reinforcement Learning »
Wilka Carvalho · Andrew Lampinen · Kyriacos Nikiforou · Felix Hill · Murray Shanahan -
2021 : SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning »
Jongjin Park · Younggyo Seo · Jinwoo Shin · Honglak Lee · Pieter Abbeel · Kimin Lee -
2022 : Allele-conditional attention mechanism for HLA-peptide complex binding affinity prediction »
Rodrigo Hormazabal · Doyeong Hwang · Kiyoung Kim · Sehui Han · Kyunghoon Bae · Honglak Lee -
2022 : Dynamics-Augmented Decision Transformer for Offline Dynamics Generalization »
Changyeon Kim · Junsu Kim · Younggyo Seo · Kimin Lee · Honglak Lee · Jinwoo Shin -
2022 : Learning Exploration Policies with View-based Intrinsic Rewards »
Yijie Guo · Yao Fu · Run Peng · Honglak Lee -
2022 : ReSPack: A Large-Scale Rectilinear Steiner Tree Packing Data Generator and Benchmark »
Kanghoon Lee · Youngjoon Park · Han-Seul Jeong · Deunsol Yoon · Sunghoon Hong · Sungryull Sohn · Minu Kim · Hanbum Ko · Moontae Lee · Honglak Lee · Kyunghoon Kim · Euihyuk Kim · Seonggeon Cho · Jaesang Min · Woohyung Lim -
2022 Poster: Transferring Pre-trained Multimodal Representations with Cross-modal Similarity Matching »
Byoungjip Kim · Sungik Choi · Dasol Hwang · Moontae Lee · Honglak Lee -
2022 Poster: Pure Transformers are Powerful Graph Learners »
Jinwoo Kim · Dat Nguyen · Seonwoo Min · Sungjun Cho · Moontae Lee · Honglak Lee · Seunghoon Hong -
2022 Poster: OpenSRH: optimizing brain tumor surgery using intraoperative stimulated Raman histology »
Cheng Jiang · Asadur Chowdury · Xinhai Hou · Akhil Kondepudi · Christian Freudiger · Kyle Conway · Sandra Camelo-Piragua · Daniel Orringer · Honglak Lee · Todd Hollon -
2022 Poster: Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost »
Sungjun Cho · Seonwoo Min · Jinwoo Kim · Moontae Lee · Honglak Lee · Seunghoon Hong -
2022 Poster: UniCLIP: Unified Framework for Contrastive Language-Image Pre-training »
Janghyeon Lee · Jongsuk Kim · Hyounguk Shon · Bumsoo Kim · Seung Hwan Kim · Honglak Lee · Junmo Kim -
2022 Poster: CEDe: A collection of expert-curated datasets with atom-level entity annotations for Optical Chemical Structure Recognition »
Rodrigo Hormazabal · Changyoung Park · Soonyoung Lee · Sehui Han · Yeonsik Jo · Jaewan Lee · Ahra Jo · Seung Hwan Kim · Jaegul Choo · Moontae Lee · Honglak Lee -
2022 Expo Talk Panel: Towards learning agents for solving complex real-world tasks »
Honglak Lee -
2021 Poster: Why Do Better Loss Functions Lead to Less Transferable Features? »
Simon Kornblith · Ting Chen · Honglak Lee · Mohammad Norouzi -
2021 Poster: Improving Transferability of Representations via Augmentation-Aware Self-Supervision »
Hankook Lee · Kibok Lee · Kimin Lee · Honglak Lee · Jinwoo Shin -
2021 Poster: Successor Feature Landmarks for Long-Horizon Goal-Conditioned Reinforcement Learning »
Christopher Hoang · Sungryull Sohn · Jongwook Choi · Wilka Carvalho · Honglak Lee -
2021 Poster: Environment Generation for Zero-Shot Compositional Reinforcement Learning »
Izzeddin Gur · Natasha Jaques · Yingjie Miao · Jongwook Choi · Manoj Tiwari · Honglak Lee · Aleksandra Faust -
2020 : Panel »
· Wilka Carvalho · Judith Fan · Tejas Kulkarni · Christopher Xie -
2020 : Invited Talk: Wilka Carvalho »
Wilka Carvalho -
2020 Poster: Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards »
Yijie Guo · Jongwook Choi · Marcin Moczulski · Shengyu Feng · Samy Bengio · Mohammad Norouzi · Honglak Lee -
2020 Poster: Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning »
Guangxiang Zhu · Minghao Zhang · Honglak Lee · Chongjie Zhang -
2019 Poster: High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks »
Ruben Villegas · Arkanath Pathak · Harini Kannan · Dumitru Erhan · Quoc V Le · Honglak Lee -
2018 Poster: A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks »
Kimin Lee · Kibok Lee · Honglak Lee · Jinwoo Shin -
2018 Spotlight: A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks »
Kimin Lee · Kibok Lee · Honglak Lee · Jinwoo Shin -
2018 Poster: Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies »
Sungryull Sohn · Junhyuk Oh · Honglak Lee -
2018 Poster: Learning Hierarchical Semantic Image Manipulation through Structured Representations »
Seunghoon Hong · Xinchen Yan · Thomas Huang · Honglak Lee -
2018 Poster: Content preserving text generation with attribute controls »
Lajanugen Logeswaran · Honglak Lee · Samy Bengio -
2017 : Invited Talk 5 »
Honglak Lee -
2017 Workshop: Learning Disentangled Features: from Perception to Control »
Emily Denton · Siddharth Narayanaswamy · Tejas Kulkarni · Honglak Lee · Diane Bouchacourt · Josh Tenenbaum · David Pfau -
2017 Poster: Value Prediction Network »
Junhyuk Oh · Satinder Singh · Honglak Lee -
2016 Poster: Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision »
Xinchen Yan · Jimei Yang · Ersin Yumer · Yijie Guo · Honglak Lee -
2016 Poster: Learning What and Where to Draw »
Scott E Reed · Zeynep Akata · Santosh Mohan · Samuel Tenka · Bernt Schiele · Honglak Lee -
2016 Oral: Learning What and Where to Draw »
Scott E Reed · Zeynep Akata · Santosh Mohan · Samuel Tenka · Bernt Schiele · Honglak Lee -
2015 : Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning »
Honglak Lee -
2015 Symposium: Deep Learning Symposium »
Yoshua Bengio · Marc'Aurelio Ranzato · Honglak Lee · Max Welling · Andrew Y Ng -
2015 Poster: Deep Visual Analogy-Making »
Scott E Reed · Yi Zhang · Yuting Zhang · Honglak Lee -
2015 Poster: Action-Conditional Video Prediction using Deep Networks in Atari Games »
Junhyuk Oh · Xiaoxiao Guo · Honglak Lee · Richard L Lewis · Satinder Singh -
2015 Spotlight: Action-Conditional Video Prediction using Deep Networks in Atari Games »
Junhyuk Oh · Xiaoxiao Guo · Honglak Lee · Richard L Lewis · Satinder Singh -
2015 Oral: Deep Visual Analogy-Making »
Scott E Reed · Yi Zhang · Yuting Zhang · Honglak Lee -
2015 Poster: Learning Structured Output Representation using Deep Conditional Generative Models »
Kihyuk Sohn · Honglak Lee · Xinchen Yan -
2015 Poster: Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis »
Jimei Yang · Scott E Reed · Ming-Hsuan Yang · Honglak Lee -
2014 Workshop: Representation and Learning Methods for Complex Outputs »
Richard Zemel · Dale Schuurmans · Kilian Q Weinberger · Yuhong Guo · Jia Deng · Francesco Dinuzzo · Hal Daumé III · Honglak Lee · Noah A Smith · Richard Sutton · Jiaqian YU · Vitaly Kuznetsov · Luke Vilnis · Hanchen Xiong · Calvin Murdock · Thomas Unterthiner · Jean-Francis Roy · Martin Renqiang Min · Hichem SAHBI · Fabio Massimo Zanzotto -
2014 Poster: Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning »
Xiaoxiao Guo · Satinder Singh · Honglak Lee · Richard L Lewis · Xiaoshi Wang -
2014 Poster: Improved Multimodal Deep Learning with Variation of Information »
Kihyuk Sohn · Wenling Shang · Honglak Lee -
2013 Poster: Robust Image Denoising with Multi-Column Deep Neural Networks »
Forest Agostinelli · Michael R Anderson · Honglak Lee -
2012 Poster: Learning to Align from Scratch »
Gary B Huang · Marwan A Mattar · Honglak Lee · Erik Learned-Miller -
2010 Workshop: Deep Learning and Unsupervised Feature Learning »
Honglak Lee · Marc'Aurelio Ranzato · Yoshua Bengio · Geoffrey E Hinton · Yann LeCun · Andrew Y Ng -
2009 Poster: Unsupervised feature learning for audio classification using convolutional deep belief networks »
Honglak Lee · Peter Pham · Yan Largman · Andrew Y Ng -
2007 Poster: Sparse deep belief net model for visual area V2 »
Honglak Lee · Ekanadham Chaitanya · Andrew Y Ng -
2006 Poster: Efficient sparse coding algorithms, end-stopping and nCRF surround suppression »
Honglak Lee · Alexis Battle · Raina Rajat · Andrew Y Ng