Transforming a nation of 1.4 billion people into the world's leading R&D hub is a monumental task. But by liberating the minds of the next generation of Indian scientists at 11, 12, and 13 years old, ...

Abstract: In scenarios where multiple decision-makers operate within a common decision space, each focusing on their own multi-objective optimization problem (e.g., bargaining games), the problem can ...

When it comes to the role of AI in our lives, the conundrum we have to crack is if—and how consciously—we inhabit our own minds.

This repository implement MFEA-II MFEA-II Official Matlab Version. Tested on MTSOO benchmark. This repo could be used as a template or starter code for conducting multitasking optimization on other ...

EvoToolkit is a Python library that leverages Large Language Models (LLMs) to evolve solutions for optimization problems. It combines the power of evolutionary algorithms with LLM-based solution ...

Abstract: Evolutionary multitask optimization (EMTO) can solve multiple tasks simultaneously by leveraging the relevant information between tasks, but existing EMTO algorithms do not take into account ...

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 ...

Chances are, you’ve seen clicks to your website from organic search results decline since about May 2024—when AI Overviews launched. Large language model optimization (LLMO), a set of tactics for ...

A new evolutionary technique from Japan-based AI lab Sakana AI enables developers to augment the capabilities of AI models without costly training and fine-tuning processes. The technique, called ...

Collective behavior is ubiquitous and highly structured in the natural world, allowing individuals to coordinate and cooperate in pursuit of common aims. The field of evolutionary game theory helps ...