Overview: Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...
A hybrid geothermal–biomass system integrates multigeneration heating, cooling, and power through thermodynamic and economic optimization.
The system's ability to learn and adapt from operational data resulted in continuous performance improvements over time. Hospital administrators reported significant reductions in scheduling conflicts ...
In this blog, we will discuss how Keysight RF Circuit Simulation Professional revamps RF circuit simulation and optimization. Discover how to achieve efficient, accurate designs for even the most ...
Abstract: Optimizing Python code is essential for enhancing performance and efficiency. This project investigates the use of large pre-trained language models, specifically GPT (Generative Pre-trained ...
Particle Swarm Optimization (PSO) Differential Evolution (DE) Many Optimizing Liaisons (MOL) - A simple variant of PSO Pattern Search (PS) Local Unimodal Sampling (LUS) All these optimizers perform ...
Aligning large language models (LLMs) with human values and preferences is challenging. Traditional methods, such as Reinforcement Learning from Human Feedback (RLHF), have paved the way by ...
Designing computational workflows for AI applications, such as chatbots and coding assistants, is complex due to the need to manage numerous heterogeneous parameters, such as prompts and ML ...
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