ArnoldArnold - DOOM Agent
Stars: ✭ 457 (-61.21%)
Rl4jDeep Reinforcement Learning for the JVM (Deep-Q, A3C)
Stars: ✭ 330 (-71.99%)
LearningxDeep & Classical Reinforcement Learning + Machine Learning Examples in Python
Stars: ✭ 241 (-79.54%)
Doom Net PytorchReinforcement learning models in ViZDoom environment
Stars: ✭ 113 (-90.41%)
Amazon Sagemaker ExamplesExample 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Stars: ✭ 6,346 (+438.71%)
MalibA Multi-agent Learning Framework
Stars: ✭ 58 (-95.08%)
TictactoeTic Tac Toe Machine Learning
Stars: ✭ 56 (-95.25%)
Mabalgs👤 Multi-Armed Bandit Algorithms Library (MAB) 👮
Stars: ✭ 67 (-94.31%)
Reporting Services Examples📕 Various example reports I use for SQL Server Reporting Services (SSRS) as well as documents for unit testing, requirements and a style guide template.
Stars: ✭ 63 (-94.65%)
DqnImplementation of q-learning using TensorFlow
Stars: ✭ 53 (-95.5%)
Learning2runOur NIPS 2017: Learning to Run source code
Stars: ✭ 57 (-95.16%)
Reinforcement LearningImplementation of Reinforcement Learning algorithms in Python, based on Sutton's & Barto's Book (Ed. 2)
Stars: ✭ 55 (-95.33%)
Ohloh apiOhloh API examples
Stars: ✭ 64 (-94.57%)
ReinforcepyCollection of reinforcement learners implemented in python. Mainly including DQN and its variants
Stars: ✭ 54 (-95.42%)
MarkovjsReinforcement Learning in JavaScript
Stars: ✭ 69 (-94.14%)
Drivebottensorflow deep RL for driving a rover around
Stars: ✭ 62 (-94.74%)
Sdcc ExamplesCode examples for microcontrollers ready to compile with SDCC
Stars: ✭ 51 (-95.67%)
MaxCode for reproducing experiments in Model-Based Active Exploration, ICML 2019
Stars: ✭ 61 (-94.82%)
Gym MinigridMinimalistic gridworld package for OpenAI Gym
Stars: ✭ 1,047 (-11.12%)
PgdrivePGDrive: an open-ended driving simulator with infinite scenes from procedural generation
Stars: ✭ 60 (-94.91%)
Personae📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.
Stars: ✭ 1,140 (-3.23%)
Nlg RlAccelerated Reinforcement Learning for Sentence Generation by Vocabulary Prediction
Stars: ✭ 59 (-94.99%)
Cook JsPhysics Chapter of Javascript book
Stars: ✭ 57 (-95.16%)
TaxorlCode for paper "End-to-End Reinforcement Learning for Automatic Taxonomy Induction", ACL 2018
Stars: ✭ 57 (-95.16%)
Torch AcRecurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms A2C and PPO
Stars: ✭ 70 (-94.06%)
Ml Surveys📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
Stars: ✭ 1,063 (-9.76%)
Drl papernotesNotes and comments about Deep Reinforcement Learning papers
Stars: ✭ 65 (-94.48%)
LeapunrealmodulesLeap Motion Unreal modules and example content.
Stars: ✭ 55 (-95.33%)
DemosSome JavaScript works published as demos, mostly ML or DS
Stars: ✭ 55 (-95.33%)
DoomlauncherDoom Launcher is a doom launching utility and database for custom wads and pk3s
Stars: ✭ 63 (-94.65%)
Golang ExamplesGo(lang) examples - (explain the basics of #golang)
Stars: ✭ 1,070 (-9.17%)
Trading GymA Trading environment base on Gym
Stars: ✭ 71 (-93.97%)
NotesThe notes for Math, Machine Learning, Deep Learning and Research papers.
Stars: ✭ 53 (-95.5%)
Vuex Orm Examples NuxtThe example Nuxt application to demonstrate the use case of the Vuex ORM.
Stars: ✭ 63 (-94.65%)
Policy Gradient MethodsImplementation of Algorithms from the Policy Gradient Family. Currently includes: A2C, A3C, DDPG, TD3, SAC
Stars: ✭ 54 (-95.42%)
Docker ExamplesThere are many like it, but this one is mine.
Stars: ✭ 66 (-94.4%)
OmgifolA Python library for manipulation of Doom WAD files
Stars: ✭ 51 (-95.67%)
ExamplesA repository of runnable Node.js examples that go beyond "hello, world!"
Stars: ✭ 61 (-94.82%)
Chocolate DoomChocolate Doom is a Doom source port that is minimalist and historically accurate.
Stars: ✭ 1,052 (-10.7%)
PypownetA power network simulator with a Reinforcement Learning-focused usage.
Stars: ✭ 69 (-94.14%)
Holodeck EngineHigh Fidelity Simulator for Reinforcement Learning and Robotics Research.
Stars: ✭ 48 (-95.93%)
Galvanise zeroLearning from zero (mostly based off of AlphaZero) in General Game Playing.
Stars: ✭ 60 (-94.91%)
Spec ExamplesSome examples on using clojure.spec!
Stars: ✭ 48 (-95.93%)
GbrainGPU Javascript Library for Machine Learning
Stars: ✭ 48 (-95.93%)
DherDHER: Hindsight Experience Replay for Dynamic Goals (ICLR-2019)
Stars: ✭ 48 (-95.93%)
MujocounityReproducing MuJoCo benchmarks in a modern, commercial game /physics engine (Unity + PhysX).
Stars: ✭ 47 (-96.01%)