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Reinforcement Learning

Before diving into the details, let’s look at a high-level overview outlining vocabulary terms we’ll see come up and contrasting different methods. It would also be useful to revisit this section ...
IEEE

Continuous-Time Reinforcement Learning: New Design Algorithms With Theoretical Insights and Performance Guarantees

Abstract: Continuous-time reinforcement learning (CT-RL) methods hold great promise in real-world applications. Adaptive dynamic programming (ADP)-based CT-RL algorithms, especially their theoretical ...
IEEE

Multi-Agent Evolutionary Reinforcement Learning Based on Cooperative Games

Abstract: Despite the significant advancements in single-agent evolutionary reinforcement learning, research exploring evolutionary reinforcement learning within multi-agent systems is still in its ...
Microsoft

Agent Lightning: Adding reinforcement learning to AI agents without code rewrites

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...