all efforts have focused on supervised learning, which is difficult to generalize beyond training data. Here we introduce multi-agent reinforcement learning as an automated discovery tool of turbulence models. We demonstrate the potential of this approach on large-eddy simulations of isotropic turbulence...
Machine Learning identifies key performance indicators to drive business growth and efficiency. Performance Metrics Machine Learning Get Started Automated Financial Reporting AI Automation in finance streamlines reporting, compliance, and financial analysis. AI Automation Finance Get Started LLMs for Strategic...
Thanks to their flexibility and adaptability, multi-agent systems are ideal for roles in nearly every industry. Automated manufacturing lines: Reducing downtime with predictive maintenance AI agents that audit equipment and communicates with another agent to schedule necessary repairs Smart power grids: O...
we propose an automated heart disease diagnosis(AHDD)system that integrates a binary convolutional neural network(CNN)with a new multi-agent feature wrapper(MAFW)model.The MAFW model consists of four software agents that operate a genetic algorithm(GA),a support vector machine(SVM),and Nave Bayes...
The early difficulties with program trading in stock markets when automated trading programs created a cascade of transactions are an example of the problems ahead and the type of impact they may have on everyday life. As in that case, the solutions will come not just from the technology, but...
We have introduced a potent method for the automated discovery of closures in simulations of wall-bounded turbulent flows that uses limited data by fusing scientific computing and multi-agent reinforcement learning (SciMARL). In this method, we solve the filtered Navier–Stokes equations using LES ...
Manual orchestration costs are also avoided as the approach is automated. To facilitate decentralised optimisation and fair gain sharing we utilised deep multi-agent reinforcement learning. The main challenge of our setting is the inability of extant methods to fully evaluate the characteristic function ...
- 《Journal of Machine Learning Research》 被引量: 3642发表: 2011年 An Improved Adaptive Background Mixture Model for Real-time Tracking with Shadow Detection Real-time segmentation of moving regions in image sequences is a fundamental step in many vision systems including automated visual ...
Firstly, while AI may create new jobs in areas like data science and machine learning engineering, it will also displace many existing jobs that are routine, repetitive, or can be automated. According to a report by the McKinsey Global Institute, up to 800 million jobs could be lost worldwid...
id=VXOircx5h3}}@misc{chi2024sela,title={SELA: Tree-Search Enhanced LLM Agents for Automated Machine Learning},author={Yizhou Chi and Yizhang Lin and Sirui Hong and Duyi Pan and Yaying Fei and Guanghao Mei and Bangbang Liu and Tianqi Pang and Jacky Kwok and Ceyao Zhang and Bang Liu ...