Robust Adaptive Autonomy in Contested Environments

Abstract

The research undertaken in this YIP proposal seeks to develop theoretical underpinnings and practical algorithms for Robust Adaptive Autonomy in Contested Environments (RAACE) for mixed manned-unmanned aerial teams. The specific objectives of this YIP proposal are:Create a new computationally and spatiotemporally scalable class of BNP and BNP-inspired predictive models and algorithms for nonstationary stochastic processes with both smooth and discrete transitions. Create Nonstationary model based reinforcement learning (N-MBRL) algorithms for risk-averse adaptive decision making in contested and time-varying environments. Develop algorithms to enable autonomous agents to infer latent human sub-goals directly from human demonstrations and feedback in contested environments. Validate the developed algorithms through data-simulations, multi-agent simulations, and flight experimentation involving humans and machines working together.

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Document Details

Document Type
Technical Report
Publication Date
Sep 28, 2021
Accession Number
AD1154209

Entities

People

  • Girish Chowdhary

Organizations

  • Oklahoma State University–Stillwater

Tags

Communities of Interest

  • Autonomy
  • C4I
  • Energy and Power Technologies
  • Engineered Resilient Systems
  • Ground and Sea Platforms
  • Space

DTIC Thesaurus Topics

  • Aircrafts
  • Artificial Intelligence
  • Automata Theory
  • Bayesian Networks
  • Computational Fluid Dynamics
  • Computational Science
  • Control Systems
  • Deep Learning
  • Human-Machine Systems
  • Information Processing
  • Information Science
  • Information Systems
  • Machine Learning
  • Motion Planning
  • Network Science
  • Neural Networks
  • Two Dimensional

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Distributed Systems and Data Platform Development
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control