Learning Continuous Control in Deep Reinforcement Learning
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Updated
Nov 24, 2018 - HTML
Learning Continuous Control in Deep Reinforcement Learning
Reinforcement learning variance comparison under function approximation.
Learning to play tennis from scratch with AlphaGo Zero style self-play using DDPG
A combination of reinforcement and evolutionary learning are used in an attempt to allow autonomous vehicles to learn behaviors necessary for the navigation of an intersection in a simple 2D traffic simulator. The open source AIM4 simulator developed by the Learning Agents Research Group at The University of Texas was extended to implement a spe…
During this final project, we will build a deep neural network and use reinforcement learning to solve a cart and pole balancing problem using OpenAI. OpenAI Gym is a tookit for developing and comparing reinforcement learning algorithms that was built by OpenAI, a non-profit artificial intelligence research company founded by Elon Musk and Sam A…
Implement popular DRL algorithms (REINFORCE, PPO, DQN, Dueling Net, Prioritized Experience Replay, DDPG, MADDPG, A2C, etc.)
Udacity Nanodegree - Machine Learning - Supervised Learning, Unsupervised Learning, and Reinforcement Learning
QuestX is an AI-powered adaptive quiz platform that generates dynamic multimodal flashcards (text, audio, video) from unstructured inputs. Built with Python, React + Vite, and Flask, it uses reinforcement learning to adjust quiz difficulty in real-time and tailors study resource recommendations based on user performance.
Udacity Machine Learning Nanodegree Project
Deep Reinforcement Learning using pytorch - Bananas
Konark Karna | AI Blog
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