SHITIANYU-hue

Data-driven-control

A reliable controller is critical for execution of safe and smooth maneuvers of an autonomous vehicle. The controller must be robust to external disturbances, such as road surface, weather, wind conditions, and so on. It also needs to deal with internal variations of vehicle sub-systems, including powertrain inefficiency, measurement errors, time delay, etc. These factors introduce issues in controller performance. In this paper, a feed-forward compensator is designed via a data-driven method to model and optimize the controller’s performance. Principal Component Analysis (PCA) is applied for extracting influential features, after which a Time Delay Neural Network is adopted to predict control errors over a future time horizon. Based on the predicted error, a feedforward compensator is then designed to improve control performance. Simulation results in different scenarios show that, with the help of with the proposed feedforward compensator, the maximum path tracking error and the steering wheel angle oscillation are improved by 44.4% and 26.7%, respectively.

multiagent-particle-envs

Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

Algorithmic-Thinking

Part of the Fundamentals of Computing Specialization, Rice, Coursera

ASTGCN

Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting (ASTGCN) AAAI 2019

COMP551-Review

coursera-algorithms-part1

📖Coursera Princeton Algorithms Part 1

Coursera-Data-Mining

Data Mining - University of Illinois at Urbana-Champaign

Graph_Convolutional_LSTM

Traffic Graph Convolutional Recurrent Neural Network

gym_torcs

hello_git

hindsight-experience-replay

This is the pytorch implementation of Hindsight Experience Replay (HER) - Experiment on all fetch robotic environments.

Literature

maddpg

Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

marl_transfer

Code for paper 'Learning transferable cooperative behaviors in multi-agent teams' (ICML 2019)

mcgill-thesis-template

rmaddpg

traffic_assignment_all_or_nothing

It is an all-or-nothing algorithm for traffic assignment.

vime

Code for the paper "Curiosity-driven Exploration in Deep Reinforcement Learning via Bayesian Neural Networks"