ujust4fun Goto Github PK

abyvinod-tac-probabilisticoccupancy

Code for TAC submission on "Probabilistic Occupancy via Forward Stochastic Reachability for Markov Jump Affine Systems" https://arxiv.org/abs/1803.07180

adaptive_and_fault_tolerant_flight_control_systems

Adaptive and fault tolerant flight control with Adaptive Neural Networks

airsim

Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research

alphafold

Open source code for AlphaFold.

bilibili-plus

课程视频、PPT和源代码：侯捷C++系列；台大郭彦甫MATLAB

book

文言陰符 An Introduction to Programming in Wenyan Language

book-mathmatical-foundation-of-reinforcement-learning

This is the homepage of a new book entitled "Mathmatical Foundations of Reinforcement Learning."

books

【编程随想】收藏的电子书清单（多个学科，含下载链接）

cbig

clgen

Domain specific language (DSL) for Flightgear checklist generation

closeaircombat

An environment based on JSBSIM aimed at one-to-one close air combat.

constrained-model-predictive-control-synthesis

A set of m-files that hopefully implements the ideas given in (Lu, Li et al. 2013)

cse415-introduction-to-artificial-intelligence

Course description: Artificial intelligence is a broad field encompassing computational models of human cognition, formal systems for representing and processing symbolic information, expert systems technology, and a variety of techniques for learning, understanding signals, and solving problems. This course provides a basic introduction to key techniques: state-space search, game-playing, probabilistic reasoning, and learning. Over the last 50 years the field has grown tremendously, and this course can only scratch the surface within the field. This course begins with a discussion of what "artificial intelligence" means and how it can be useful. Next is a grounding in state-space search, problem formulation and solving. We then consider state-space search in the context of game playing, which then leads to alpha-beta pruning, expectimax search and the modeling of uncertainty. After that, we focus primarily on machine learning, starting with methods for reasoning under uncertainty. We cover learning of decision trees from examples, reinforcement learning in Markov Decision Processes, perceptron learning, and deep learning. We touch briefly on the future of AI. The teaching methodology combines lectures, in-class and out-of-class exercises, and programming assignments.

dcs-api

Digital Combat Simulator API information

deep-reinforcement-learning-algorithms-with-pytorch

PyTorch implementations of deep reinforcement learning algorithms and environments

deeprl-agents

A set of Deep Reinforcement Learning Agents implemented in Tensorflow.

dogfight-sandbox-hg2

Air to air combat sandbox, created in Python 3 using the HARFANG 3D 2 framework.

ebooks

eBook分享大集合：主要以IT领域经典书籍收藏，以备不时之需。

fixedwing-airsim

Combines JSBSim and Airsim with a python module to simulate a fixedwing

flightgear

Mirror: FlightGear - Open source flight sim

gpt-neo

An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.

installtutorial

jsbsim

An open source flight dynamics & control software library

jsbsim_rl

reinforcement learning with jsbsim and open ai baselines

jupyter-flightgear

Streaming live data from FlightGear to plots in a Jupyter notebook

littlenavmap

Little Navmap is a free flight planner, navigation tool, moving map, airport search and airport information system for Flight Simulator X and Prepar3D.

machinelearning

My blogs and code for machine learning. http://cnblogs.com/pinard

markov-pilot

A reinforcement learning environment for aircraft control using the JSBSim flight dynamics model

mathnet-numerics

Math.NET Numerics

mjls

Reference implementations of (my) control algorithms for Markov Jump Linear Systems without mode observation.