Electronic Design

“Reinforcement Learning” Fuels the Rise of Adaptive Controllers

More engineers are turning to reinforcement learning to incorporate adaptive and self-tuning control into industrial systems. It aims to strike a balance between traditional ...
IEEE

Reinforcement Learning for Game-Theoretic Resource Allocation on Graphs

Abstract: Game-theoretic resource allocation on graphs (GRAG) involves two players competing over multiple steps to control nodes of interest on a graph, a problem modeled as a multi-step Colonel ...
IEEE

Leaky PPO: A Simple and Efficient RL Algorithm for Autonomous Vehicles

Abstract: Interest in applying Reinforcement Learning (RL) to Autonomous Vehicles (AVs) is experiencing a rapid and substantial expansion. Proximal Policy Optimization (PPO), a well-known RL algorithm ...
GitHub

Reinforcement learning in portfolio management

Motivated by "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem" by Jiang et. al. 2017 [1]. In this project: Implement three state-of-art continous deep ...
blockchain

DeepMind Unveils AI System That Discovers Novel Reinforcement Learning Algorithms, Surpassing Human Designs

According to God of Prompt on Twitter, DeepMind has published groundbreaking research in Nature led by David Silver, introducing an AI meta-learning system capable of autonomously discovering entirely ...
marktechpost

Microsoft Releases Agent Lightning: A New AI Framework that Enables Reinforcement Learning (RL)-based Training of LLMs for Any AI Agent

How do you convert real agent traces into reinforcement learning RL transitions to improve policy LLMs without changing your existing agent stack? Microsoft AI team releases Agent Lightning to help ...
pv magazine International

Optimizing solar-plus-storage operation for markets with imbalance penalties

Researchers from Japan’s University of Tsukuba have developed a novel imbalance-aware control framework for photovoltaic battery storage systems (PV-BSS) that trade in day-ahead electricity markets ...
marktechpost

Stanford Researchers Released AgentFlow: In-the-Flow Reinforcement Learning RL for Modular, Tool-Using AI Agents

Flow-GRPO (Flow-based Group Refined Policy Optimization) converts long-horizon, sparse-reward optimization into tractable single-turn updates: Benchmarks. The research team evaluates four task types: ...