AI2-THOR: An Interactive 3D Environment for Visual AI
- Eric Kolve, Roozbeh Mottaghi, Ali Farhadi
- Computer ScienceArXiv
- 14 December 2017
AI2-THOR consists of near photo-realistic 3D indoor scenes, where AI agents can navigate in the scenes and interact with objects to perform tasks and facilitate building visually intelligent models.
RoboTHOR: An Open Simulation-to-Real Embodied AI Platform
- Matt Deitke, Winson Han, Ali Farhadi
- Computer ScienceComputer Vision and Pattern Recognition
- 14 April 2020
RoboTHOR offers a framework of simulated environments paired with physical counterparts to systematically explore and overcome the challenges of simulation-to-real transfer, and a platform where researchers across the globe can remotely test their embodied models in the physical world.
ManipulaTHOR: A Framework for Visual Object Manipulation
- Kiana Ehsani, Winson Han, Roozbeh Mottaghi
- Computer ScienceComputer Vision and Pattern Recognition
- 22 April 2021
This work proposes a framework for object manipulation built upon the physics-enabled, visually rich AI2-THOR framework and presents a new challenge to the Embodied AI community known as ArmPointNav, which extends the popular point navigation task to object manipulation and offers new challenges including 3D obstacle avoidance.
Learning Generalizable Visual Representations via Interactive Gameplay
- Luca Weihs, Aniruddha Kembhavi, Ali Farhadi
- Computer ScienceInternational Conference on Learning…
- 2021
Artificial Agents Learn Flexible Visual Representations by Playing a Hiding Game
- Luca Weihs, Aniruddha Kembhavi, Ali Farhadi
- BiologyArXiv
- 17 December 2019
This work is the first to show that embodied adversarial reinforcement learning agents playing cache, a variant of hide-and-seek, in a high fidelity, interactive, environment, learn representations of their observations encoding information such as occlusion, object permanence, free space, and containment.
Beyond Sentential Semantic Parsing: Tackling the Math SAT with a Cascade of Tree Transducers
- Mark Hopkins, Cristian Petrescu-Prahova, Roie Levin, Ronan Le Bras, Alvaro Herrasti, V. Joshi
- Computer ScienceConference on Empirical Methods in Natural…
- 1 September 2017
We present an approach for answering questions that span multiple sentences and exhibit sophisticated cross-sentence anaphoric phenomena, evaluating on a rich source of such questions – the math…
ProcTHOR: Large-Scale Embodied AI Using Procedural Generation
- Matt Deitke, Eli VanderBilt, Roozbeh Mottaghi
- Computer ScienceArXiv
- 14 June 2022
The proposed PROCTHOR, a framework for procedural generation of Embodied AI environments, enables us to sample arbitrarily large datasets of diverse, interactive, customizable, and performant virtual environments to train and evaluate embodied agents across navigation, interaction, and manipulation tasks.
Interactive Visualization for Linguistic Structure
- A. Sarnat, V. Joshi, Cristian Petrescu-Prahova, Alvaro Herrasti, Brandon Stilson, Mark Hopkins
- Computer ScienceEMNLP
- 1 September 2017
The library is not tied to any particular linguistic representation, but provides a general-purpose API for the interactive exploration of hierarchical linguistic structure, and offers several important features, including expand/collapse functionality, positional and color cues, and explicit visual support for sequential structure.
Iconary: A Pictionary-Based Game for Testing Multimodal Communication with Drawings and Text
- Christopher Clark, Jordi Salvador, Ali Farhadi
- Computer ScienceEMNLP
- 1 December 2021
This work proposes models to play Iconary, a collaborative game of drawing and guessing based on Pictionary, that poses a novel challenge for the research community and proposes models that are skillful players and able to employ world knowledge in language models toplay with words unseen during training.
A Case Study in Hybrid Multi-threading and Hierarchical Reinforcement Learning Approach for Cooperative Multi-agent Systems
- Hiram Ponce, Ricardo Padilla, Alan Davalos, Alvaro Herrasti, Cynthia Pichardo, Daniel Dovali
- Computer ScienceFourteenth Mexican International Conference on…
- 25 October 2015
Experimental results show that this multi-agent system can reduce the time process and still maintain independence of agents.
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