GRASP: Global Reading and Assembly for Semantic, Probabilistic World Models

Abstract

We propose technology that reads and assembles causal, probabilistic models relevant to national and global security analysis. There is an acute need for such methods: currently most such analyses are done manually, taking years to complete. Our technology will enable analysts to quickly build and analyze such models to understand what crises are possible and how to avert them.

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Document Details

Document Type
Technical Report
Publication Date
Mar 25, 2023
Accession Number
AD1210612

Entities

People

  • Mihai Surdeanu

Organizations

  • University of Arizona

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Agriculture
  • Algorithms
  • Artificial Intelligence Software
  • Bayesian Networks
  • Climate Change
  • Climate Change Adaptation
  • Computational Linguistics
  • Computational Science
  • Computer Languages
  • Databases
  • Human-Machine Interfaces
  • Information Science
  • Language
  • Linguistics
  • Natural Language Processing
  • Neural Networks
  • Ontologies
  • Probabilistic Models
  • Probability Distributions
  • Security
  • Simulations
  • Statistical Analysis
  • Word Processors

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Database Systems and Applications
  • Systems Analysis and Design