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Saurabh Kumar's Projects

batch_rl icon batch_rl

Offline Reinforcement Learning (aka Batch Reinforcement Learning) on Atari 2600 games

bsuite icon bsuite

bsuite is a collection of carefully-designed experiments that investigate core capabilities of a reinforcement learning (RL) agent

dopamine icon dopamine

Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

fcrl icon fcrl

Implementation of "Federated Control with Hierarchical Multi-Agent Deep Reinforcement Learning" (https://arxiv.org/pdf/1712.08266.pdf)

hierarchical-dqn icon hierarchical-dqn

Implementation of the paper Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation - https://arxiv.org/pdf/1604.06057.pdf

l2_init icon l2_init

Code accompanying the paper "Maintaining Plasticity in Continual Learning via Regenerative Regularization"

learn_to_compose icon learn_to_compose

My implementation of base skill training for "Learning to Compose Skills" (https://arxiv.org/abs/1711.11289)

loss-of-plasticity icon loss-of-plasticity

Contains the implementation of continual supervised learning problem where we can show loss of plasticity in backprop

mammoth icon mammoth

An Extendible (General) Continual Learning Framework based on Pytorch - official codebase of Dark Experience for General Continual Learning

paylytics icon paylytics

Paylytics is an app that allows you to scan your receipts into our database and let us handle budgeting for you. Developed for HackGT 2015

reinforcement-learning icon reinforcement-learning

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

simplypaper.github.io icon simplypaper.github.io

MHacks V Project 2015. Nikhil Kulkarni. Anirudh Gubba. Saurabh Kumar. Advith Chelikani. Arthur Li.

state-space-decomposition icon state-space-decomposition

Codebase for RLDM 2017 paper on "State Space Decomposition and Subgoal Creation for Transfer" (https://arxiv.org/abs/1705.08997)

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