27 citations · 40 across the 2 of their papers we have counts for
8 papers
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning
Dipendra Misra, Mikael Henaff, Akshay Krishnamurthy +1
We present an algorithm, HOMER, for exploration and reinforcement learning in rich observation environments that are summarizable by an unknown latent state space. The algorithm in…
Combating the Compounding-Error Problem with a Multi-step Model
Kavosh Asadi, Dipendra Misra, Seungchan Kim +1
Model-based reinforcement learning is an appealing framework for creating agents that learn, plan, and act in sequential environments. Model-based algorithms typically involve lear…
Touchdown: Natural Language Navigation and Spatial Reasoning in Visual Street Environments
Howard Chen, Alane Suhr, Dipendra Misra +2
We study the problem of jointly reasoning about language and vision through a navigation and spatial reasoning task. We introduce the Touchdown task and dataset, where an agent mus…
Early Fusion for Goal Directed Robotic Vision
Aaron Walsman, Yonatan Bisk, Saadia Gabriel +4
Building perceptual systems for robotics which perform well under tight computational budgets requires novel architectures which rethink the traditional computer vision pipeline. M…
Towards a Simple Approach to Multi-step Model-based Reinforcement Learning
Kavosh Asadi, Evan Cater, Dipendra Misra +1
When environmental interaction is expensive, model-based reinforcement learning offers a solution by planning ahead and avoiding costly mistakes. Model-based agents typically learn…
Policy Shaping and Generalized Update Equations for Semantic Parsing from Denotations
Dipendra Misra, Ming-Wei Chang, Xiaodong He +1
Semantic parsing from denotations faces two key challenges in model training: (1) given only the denotations (e.g., answers), search for good candidate semantic parses, and (2) cho…