Search Results for author: Tanmay Shankar

Found 4 papers, 1 papers with code

Learning Robot Skills with Temporal Variational Inference

no code implementations ICML 2020 Tanmay Shankar, Abhinav Gupta

In this paper, we address the discovery of robotic options from demonstrations in an unsupervised manner.

Variational Inference

Discovering Motor Programs by Recomposing Demonstrations

no code implementations ICLR 2020 Tanmay Shankar, Shubham Tulsiani, Lerrel Pinto, Abhinav Gupta

In this paper, we present an approach to learn recomposable motor primitives across large-scale and diverse manipulation demonstrations.

Hierarchical Reinforcement Learning

Learning Neural Parsers with Deterministic Differentiable Imitation Learning

no code implementations20 Jun 2018 Tanmay Shankar, Nicholas Rhinehart, Katharina Muelling, Kris M. Kitani

We introduce a novel deterministic policy gradient update, DRAG (i. e., DeteRministically AGgrevate) in the form of a deterministic actor-critic variant of AggreVaTeD, to train our neural parser.

Imitation Learning

Reinforcement Learning via Recurrent Convolutional Neural Networks

1 code implementation9 Jan 2017 Tanmay Shankar, Santosha K. Dwivedy, Prithwijit Guha

Deep Reinforcement Learning has enabled the learning of policies for complex tasks in partially observable environments, without explicitly learning the underlying model of the tasks.

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