aadharna
PhD student at UBC. Interested in reinforcement learning, generative models, open-endedness, and the intersection of games and machine learning.
University of British ColumbiaNew York, NY / Vancouver, BC
aadharna's Stars
cvxgrp/cvxpylayers
Differentiable convex optimization layers
PufferAI/PufferLib
Simplifying reinforcement learning for complex game environments
rail-berkeley/softlearning
Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.
hrpan/tetris_mcts
MCTS project for Tetris
leopard-ai/betty
Betty: an automatic differentiation library for generalized meta-learning and multilevel optimization
Bam4d/Griddly
A grid-world game engine for game AI research
Bam4d/Neural-Game-Engine
Code to reproduce Neural Game Engine experiments and pre-trained models
ollebompa/PGA-MAP-Elites
Repository for the PGA-MAP-Elites algorithm. PGA-MAP-Elites was developed to efficiently scale MAP-Elites to large genotypes and noisy domains. It uses Neuroevolution driven by a Genetic Algorithm (GA) coupled with Policy Gradients (PG) derived from an off-policy Deep Reinforcement Learning method.
ajohnston9/kNNFastDTW
An implementation of kNN with FastDTW as distance measurement