Statistical Model Checking for Swarms-Input Attribution

Abstract

Input Attribution The Why of SMC Statistical Model Checking (SMC) provides an estimate on the probability [] that a predicate in a model is satised, but does not address why a particular result was obtained. The goal of Input Attribution (IA) is to use machine learning techniques to synthesize an explanation for an SMC result in terms of the inputs. IA for SMC can be thought of as analogous to the counter-example in traditional model checking.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2016
Accession Number
AD1105822

Entities

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Engineered Resilient Systems

DTIC Thesaurus Topics

  • Accuracy
  • Data Science
  • Environment
  • Errors
  • Indicators
  • Information Science
  • Learning
  • Machine Learning
  • Mathematics
  • Polynomials
  • Probability
  • Servers (Computer Hardware)
  • Simulations
  • Simulators
  • Standards
  • Validation

Readers

  • Aerospace Engineering.
  • Mathematical Modeling and Probability Theory.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference