Reinforcement
Artificial Intelligence
The Many Faces of Reinforcement Learning: Shaping Large Language Models
Lately, Large Language Models (LLMs) have significantly redefined the sphere of artificial intelligence (AI), enabling machines to know and generate human-like text with remarkable proficiency. This success is basically attributed to advancements in machine...
Artificial Intelligence
DeepSeek-R1: Transforming AI Reasoning with Reinforcement Learning
DeepSeek-R1 is the groundbreaking reasoning model introduced by China-based DeepSeek AI Lab. This model sets a brand new benchmark in reasoning capabilities for open-source AI. As detailed within the accompanying research paper, DeepSeek-R1 evolves...
Artificial Intelligence
Jointly learning rewards and policies: an iterative Inverse Reinforcement Learning framework with ranked synthetic trajectories
2.1 Apprenticeship Learning:A seminal method to learn from expert demonstrations is Apprenticeship learning, first introduced in . Unlike pure Inverse Reinforcement Learning, the target here is to each to search out the optimal reward...
Artificial Intelligence
Reinforcement Learning for Physics: ODEs and Hyperparameter Tuning
Working with ODEsPhysical systems can typically be modeled through differential equations, or equations including derivatives. Forces, hence Newton’s Laws, might be expressed as derivatives, as can Maxwell’s Equations, so differential equations can describe most...
Artificial Intelligence
Monte Carlo Methods for Solving Reinforcement Learning Problems
Dissecting “Reinforcement Learning” by Richard S. Sutton with Custom Python Implementations, Episode IIIWe proceed our deep dive into Sutton’s great book about RL and here deal with Monte Carlo (MC) methods. These are...
Artificial Intelligence
Reinforcement Learning, Part 7: Introduction to Value-Function Approximation
Scaling reinforcement learning from tabular methods to large spacesReinforcement learning is a site in machine learning that introduces the concept of an agent learning optimal strategies in complex environments. The agent learns from its...
Artificial Intelligence
Reinforcement Learning, Part 5: Temporal-Difference Learning
Intelligently synergizing dynamic programming and Monte Carlo algorithms15 min read·15 hours agoReinforcement learning is a website in machine learning that introduces the concept of an agent learning optimal strategies in complex environments. The agent...
Artificial Intelligence
Deep Reinforcement Learning: Toward Integrated and Unified AI
Can AI provide a lens on human intelligence?Proceed reading on Towards Data Science »
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