Electronics360

Wind turbine control systems: From PID to reinforcement learning

In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...
eLife

A differentiable model for optimizing the genetic drivers of synaptogenesis

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...
IEEE

Double Successive Over-Relaxation Q-Learning With an Extension to Deep Reinforcement Learning

Abstract: Q-learning (QL) is a widely used algorithm in reinforcement learning (RL), but its convergence can be slow, especially when the discount factor is close to one. Successive over-relaxation ...
marktechpost

Weak-for-Strong (W4S): A Novel Reinforcement Learning Algorithm that Trains a weak Meta Agent to Design Agentic Workflows with Stronger LLMs

W4S operates in turns. The state contains task instructions, the current workflow program, and feedback from prior executions. An action has 2 components, an analysis of what to change, and new Python ...
Frontiers

Intelligent maneuver decision-making for UAVs using the TD3–LSTM reinforcement learning algorithm under uncertain information

Aiming to address the complexity and uncertainty of unmanned aerial vehicle (UAV) aerial confrontation, a twin delayed deep deterministic policy gradient (TD3)–long short-term memory (LSTM) ...
Frontiers

A novel reinforcement learning framework-based path planning algorithm for unmanned surface vehicle

Unmanned surface vehicles (USVs) nowadays have been widely used in ocean observation missions, helping researchers to monitor climate change, collect environmental data, and observe marine ecosystem ...
C&EN

Reinforcement Learning-Based Nonlinear Model Predictive Controller for a Jacketed Reactor: A Machine Learning Concept Validation Using Jetson Orin

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this research work authors have experimentally validated a blend of Machine ...
Ars Technica

How a big shift in training LLMs led to a capability explosion

In April 2023, a few weeks after the launch of GPT-4, the Internet went wild for two new software projects with the audacious names BabyAGI and AutoGPT. “Over the past week, developers around the ...
eLife

Dynamics of striatal action selection and reinforcement learning

The authors present a biologically plausible framework for action selection and learning in the striatum that is a fundamental advance in our understanding of possible neural implementations of ...