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Ankesh Anand

Alumni

Publications

Blindfold Baselines for Embodied QA
Ankesh Anand
Eugene Belilovsky
Kyle Kastner
Hugo Larochelle
Aaron Courville
We explore blindfold (question-only) baselines for Embodied Question Answering. The EmbodiedQA task requires an agent to answer a question b… (voir plus)y intelligently navigating in a simulated environment, gathering necessary visual information only through first-person vision before finally answering. Consequently, a blindfold baseline which ignores the environment and visual information is a degenerate solution, yet we show through our experiments on the EQAv1 dataset that a simple question-only baseline achieves state-of-the-art results on the EmbodiedQA task in all cases except when the agent is spawned extremely close to the object.
2018-11-12
ArXiv (prépublication)
arxiv.org
arxiv.org
HoME: a Household Multimodal Environment
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… (voir plus) with objects and other agents, all within a realistic context. HoME integrates over 45,000 diverse 3D house layouts based on the SUNCG dataset, a scale which may facilitate learning, generalization, and transfer. HoME is an open-source, OpenAI Gym-compatible platform extensible to tasks in reinforcement learning, language grounding, sound-based navigation, robotics, multi-agent learning, and more. We hope HoME better enables artificial agents to learn as humans do: in an interactive, multimodal, and richly contextualized setting.
2018-01-01
ICLR (Workshop) (publié)
openreview.net
openreview.net