Persistent Evolution of Molecules Using Evolutionary Multi-Objective Optimization with Machine Learning Techniques

Abstract

The search space of molecular structure is quite large, although the variety of the type ofconstituent atoms are limited due to the graph search. By combining evolutionary computation and machine learning methods, i.e., graph kernel, Monte Carlo tree search, and Quantum Deep Field which is a fusion of frontier orbit theory and deep learning.

Document Details

Document Type
DoD Grant Award
Publication Date
Feb 05, 2025
Source ID
FA23862414038

Entities

People

  • Hisashi Handa

Organizations

  • Air Force Office of Scientific Research
  • Kindai University
  • United States Air Force

Tags

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Computational Fluid Dynamics (CFD)
  • Operations Research

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Neural Networks
  • Quantum Computing
  • Space
  • Space - Space Objects