Nutshell reports that cloud innovations simplify CRM implementation, enabling quick setup and user adoption for businesses of ...

Advanced AI systems can appear helpful while learning behaviors that look deceptive, self-protective, or manipulative.

Abstract: Different from most other dynamic multi-objective optimization problems (DMOPs), DMOPs with a changing number of objectives usually result in expansion or contraction of the Pareto front or ...

Gartner predicted traditional search volume will drop 25% this year as users shift to AI-powered answer engines. Google’s AI Overviews now reach more than 2 billion monthly users, ChatGPT serves 800 ...

Management of groundwater quality in agricultural areas requires tradeoffs between competing objectives. These objectives include economic benefit, respect for regulatory-imposed water quality ...

In this tutorial, we implement an advanced Optuna workflow that systematically explores pruning, multi-objective optimization, custom callbacks, and rich visualization. Through each snippet, we see ...

In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...

Tourism development in emerging destinations requires balancing economic benefits with ecological sustainability. In this study, we investigate the case of multi-attraction tourism planning in Qujing ...

Abstract: Multi-party multi-objective optimization, which aims to find a solution set that satisfies multiple decision makers (DMs) as much as possible, has attracted the attention of researchers ...

This repository contains the code to run the experiments in the paper (Buckingham et al., 2025): Buckingham, J. M., Rojas Gonzalez, S., & Branke, J. (2025). Knowledge Gradient for Multi-Objective ...