Search Results for author: Florian Golemo

Found 19 papers, 8 papers with code

The Sandbox Environment for Generalizable Agent Research (SEGAR)

1 code implementation19 Mar 2022 R Devon Hjelm, Bogdan Mazoure, Florian Golemo, Felipe Frujeri, Mihai Jalobeanu, Andrey Kolobov

A broad challenge of research on generalization for sequential decision-making tasks in interactive environments is designing benchmarks that clearly landmark progress.

Decision Making

GrowSpace: Learning How to Shape Plants

no code implementations15 Oct 2021 Yasmeen Hitti, Ionelia Buzatu, Manuel Del Verme, Mark Lefsrud, Florian Golemo, Audrey Durand

We argue that plant responses to an environmental stimulus are a good example of a real-world problem that can be approached within a reinforcement learning (RL)framework.

Fairness

Touch-based Curiosity for Sparse-Reward Tasks

1 code implementation1 Apr 2021 Sai Rajeswar, Cyril Ibrahim, Nitin Surya, Florian Golemo, David Vazquez, Aaron Courville, Pedro O. Pinheiro

Robots in many real-world settings have access to force/torque sensors in their gripper and tactile sensing is often necessary in tasks that involve contact-rich motion.

Visual Imitation with Reinforcement Learning using Recurrent Siamese Networks

no code implementations1 Jan 2021 Glen Berseth, Florian Golemo, Christopher Pal

It would be desirable for a reinforcement learning (RL) based agent to learn behaviour by merely watching a demonstration.

One-Shot Learning reinforcement-learning

Visual Question Answering From Another Perspective: CLEVR Mental Rotation Tests

no code implementations1 Jan 2021 Christopher Beckham, Martin Weiss, Florian Golemo, Sina Honari, Derek Nowrouzezahrai, Christopher Pal

To do this we have created a new version of the CLEVR VQA problem setup and dataset that we call CLEVR Mental Rotation Tests or CLEVR-MRT, where the goal is to answer questions about the original CLEVR viewpoint given a single image obtained from a different viewpoint of the same scene.

3D Reconstruction Contrastive Learning +4

Perspectives on Sim2Real Transfer for Robotics: A Summary of the R:SS 2020 Workshop

no code implementations7 Dec 2020 Sebastian Höfer, Kostas Bekris, Ankur Handa, Juan Camilo Gamboa, Florian Golemo, Melissa Mozifian, Chris Atkeson, Dieter Fox, Ken Goldberg, John Leonard, C. Karen Liu, Jan Peters, Shuran Song, Peter Welinder, Martha White

This report presents the debates, posters, and discussions of the Sim2Real workshop held in conjunction with the 2020 edition of the "Robotics: Science and System" conference.

Pix2Shape: Towards Unsupervised Learning of 3D Scenes from Images using a View-based Representation

1 code implementation23 Mar 2020 Sai Rajeswar, Fahim Mannan, Florian Golemo, Jérôme Parent-Lévesque, David Vazquez, Derek Nowrouzezahrai, Aaron Courville

We propose Pix2Shape, an approach to solve this problem with four components: (i) an encoder that infers the latent 3D representation from an image, (ii) a decoder that generates an explicit 2. 5D surfel-based reconstruction of a scene from the latent code (iii) a differentiable renderer that synthesizes a 2D image from the surfel representation, and (iv) a critic network trained to discriminate between images generated by the decoder-renderer and those from a training distribution.

Generating Automatic Curricula via Self-Supervised Active Domain Randomization

1 code implementation18 Feb 2020 Sharath Chandra Raparthy, Bhairav Mehta, Florian Golemo, Liam Paull

Goal-directed Reinforcement Learning (RL) traditionally considers an agent interacting with an environment, prescribing a real-valued reward to an agent proportional to the completion of some goal.

Robo-PlaNet: Learning to Poke in a Day

no code implementations9 Nov 2019 Maxime Chevalier-Boisvert, Guillaume Alain, Florian Golemo, Derek Nowrouzezahrai

Recently, the Deep Planning Network (PlaNet) approach was introduced as a model-based reinforcement learning method that learns environment dynamics directly from pixel observations.

Model-based Reinforcement Learning reinforcement-learning

Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments

1 code implementation29 Oct 2019 Martin Weiss, Simon Chamorro, Roger Girgis, Margaux Luck, Samira E. Kahou, Joseph P. Cohen, Derek Nowrouzezahrai, Doina Precup, Florian Golemo, Chris Pal

In our endeavor to create a navigation assistant for the BVI, we found that existing Reinforcement Learning (RL) environments were unsuitable for the task.

Pix2Scene: Learning Implicit 3D Representations from Images

no code implementations ICLR 2019 Sai Rajeswar, Fahim Mannan, Florian Golemo, David Vazquez, Derek Nowrouzezahrai, Aaron Courville

Modelling 3D scenes from 2D images is a long-standing problem in computer vision with implications in, e. g., simulation and robotics.

Active Domain Randomization

1 code implementation9 Apr 2019 Bhairav Mehta, Manfred Diaz, Florian Golemo, Christopher J. Pal, Liam Paull

Our experiments show that domain randomization may lead to suboptimal, high-variance policies, which we attribute to the uniform sampling of environment parameters.

Towards Learning to Imitate from a Single Video Demonstration

no code implementations22 Jan 2019 Glen Berseth, Florian Golemo, Christopher Pal

We approach this challenge using contrastive training to learn a reward function comparing an agent's behaviour with a single demonstration.

Imitation Learning One-Shot Learning

HoME: a Household Multimodal Environment

no code implementations29 Nov 2017 Simon Brodeur, Ethan Perez, Ankesh Anand, Florian Golemo, Luca Celotti, Florian Strub, Jean Rouat, Hugo Larochelle, Aaron Courville

We introduce HoME: a Household Multimodal Environment for artificial agents to learn from vision, audio, semantics, physics, and interaction with objects and other agents, all within a realistic context.

OpenAI Gym reinforcement-learning

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