Abstract: To address the energy supply challenges of online monitoring devices for power cables, a self-powering solution based on magnetic induction energy harvesting device is proposed.

This study from MIT explores eye evolution through AI simulations, uncovering how different tasks shape visual systems and ...

A Reinforcement Machine Learning Minesweeper Algorithm written in Java. It learns Minesweeper by failing repeatedly and learning from its mistakes. It scans a Minesweeper board for subsets of numbers, ...

AgiBot announced a key milestone this week with the successful deployment of its Real-World Reinforcement Learning system in a manufacturing pilot with Longcheer Technology. The pilot project marks ...

Reinforcement learning (RL) is machine learning (ML) in which the learning system adjusts its behavior to maximize the amount of reward and minimize the amount of punishment it receives over time ...

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 ...

Abstract: The discovery of community structure in complex networks has become a hotspot in recent years. As an NP-hard problem, community detection can be solved by multiobjective evolutionary ...

Reinforcement learning (RL) plays a crucial role in scaling language models, enabling them to solve complex tasks such as competition-level mathematics and programming through deeper reasoning.

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 ...

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) ...