Basic Kinematics of Mice Reinforcement Learning in Intelligent Cages
Explore reinforcement learning in mice using intelligent cages, combining point processes and behavioral analysis to study learning and social aspects in experimental settings.
Recent Progress in Continuous-Time Reinforcement Learning and Regret Analysis
Explore recent advancements in continuous-time reinforcement learning and regret analysis, focusing on mathematical applications in economics and finance.
Reinforcement Learning with Human Feedback
Explore how human feedback enhances AI models, improving text generation and responsiveness. Learn RLHF techniques for fine-tuning large language models with Luis Serrano, PhD.
Robust Design Discovery and Exploration in Bayesian Optimization
Explore data-driven methods for robust design discovery and optimization, focusing on Bayesian techniques that efficiently handle uncertainties and adversarial scenarios in various scientific domains.
Fixed-point Error Bounds for Mean-payoff Markov Decision Processes
Explore optimal transport techniques for deriving finite-time error bounds in reinforcement learning, focusing on mean-payoff Markov decision processes and stochastic fixed point iterations.
Learning to Fly High: Reinforcement Learning for Soaring and Airborne Wind Energy
Explore reinforcement learning for soaring and airborne wind energy, focusing on optimal control strategies in turbulent atmospheric conditions.
Introduction to Artificial Intelligence: Reinforcement Learning - Lecture 13
Explore reinforcement learning fundamentals, including key concepts, problem specifications, and practical examples like Cart Pole and Mountain Car. Gain insights into policies, rewards, and the exploration-exploitation trade-off.
Intro to Artificial Intelligence - MDP and Dynamic Programming - Lecture 15
Explore Markov Decision Processes and Dynamic Programming in AI, learning algorithmic techniques for modern problem-solving in game environments.
Introduction to Artificial Intelligence: Monte Carlo Reinforcement Learning Methods - Lecture 16
Explore Monte Carlo reinforcement learning methods, including prediction and policy iteration, with applications to Blackjack and matchbox machine learning.
Introduction to Artificial Intelligence: Deep Neural Networks - Lecture 19
Explore deep neural networks, edge detection, and reinforcement learning in AI, with applications to games and image processing.
COMP3200 - Introduction to Artificial Intelligence - MDP and Dynamic Programming - Lecture 16
Explore Markov Decision Processes and Dynamic Programming in AI, learning algorithmic techniques for modern problem-solving in game environments.
Intro to Artificial Intelligence - RL Monte Carlo Methods - Lecture 17
Explore Monte Carlo methods in reinforcement learning, applying algorithmic techniques to solve AI problems in gaming environments.
Introduction to Artificial Intelligence - Lecture 14: Assignment 4
Explore algorithmic techniques and data structures for AI problem-solving, applying learned concepts to simple games in this graduate-level introduction to Artificial Intelligence.
Introduction to Artificial Intelligence - Lecture 15: Intro to Reinforcement Learning
Explore reinforcement learning fundamentals, including key concepts and applications in AI problem-solving environments for modern algorithmic techniques.
Introduction to Artificial Intelligence - Bandit Algorithms - Lecture 16
Explore bandit algorithms in AI, learning key techniques for optimizing decision-making in uncertain environments through practical applications and examples.
Intro to Artificial Intelligence - Markov Decision Process (MDP) - Lecture 17
Explore Markov Decision Processes (MDPs) in AI, learning algorithmic techniques for modern problem-solving in uncertain environments.
Collaborative Songwriting and Production with Symbolic Generative AI
Explore cutting-edge techniques for integrating generative AI into collaborative songwriting and music production. Learn about symbolic generation, AI-generated MIDI, and innovative approaches to augment creativity.
FastCFE - A Counterfactual Explainer Using Reinforcement Learning
Explore reinforcement learning for real-time counterfactual explanations in machine learning explainability. Learn about FastCFE algorithm, OpenAI Gym, and Ray+RLlib for actionable insights in various applications.
Gearing Up for FIFA 2022 Using RLlib-Powered Traffic Control
Optimize traffic control for FIFA 2022 using RLlib-powered multi-agent reinforcement learning, microsimulation, and Graph Convolutional Networks for congestion management in Qatar.
Large-Scale Deep Learning to Augment Production RL Workloads at Riot Games
Learn to leverage large-scale deep learning for building game bots, predicting outcomes, and optimizing training processes in game development. Explore supervised learning techniques and scaling with Ray tools.
Ray/RLLib-Empowered Reinforcement Learning Based Recommender Systems in NetEase Game
Explore how Ray/RLLib enhances reinforcement learning-based recommender systems in NetEase Games, improving user experience and profitability. Learn about the open-source RL4RS dataset for training and evaluating RL algorithms.