output
20222025
most citedSystems Theoretic Process Analysis of a Run Time Assured Neural Network Control System

7 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

8 papers

astro-ph.HE2025★ 3 cited

What determines the -ray luminosities of classical novae?

Peter Craig, Elias Aydi, Laura Chomiuk +25

Classical novae in the Milky Way have now been well-established as high-energy GeV -ray sources. In novae with main-sequence companions, this emission is believed to result from…

cs.AI2025

Sensemaking in Novel Environments: How Human Cognition Can Inform Artificial Agents

Robert E. Patterson, Regina Buccello-Stout, Mary E. Frame +8

One of the most vital cognitive skills to possess is the ability to make sense of objects, events, and situations in the world. In the current paper, we offer an approach for creat…

cs.MS2024

SequentialSamplingModels.jl: Simulating and Evaluating Cognitive Models of Response Times in Julia

Kianté Fernandez, Dominique Makowski, Christopher Fisher

Sequential sampling models (SSMs) are a widely used framework describing decision-making as a stochastic, dynamic process of evidence accumulation. SSMs popularity across cognitive…

astro-ph.SR2024★ 2 cited

VLBI detection of nearby (< 100 pc) young stars: Pilot observations

Sergio A. Dzib, Laurent Loinard, Ralf Launhardt +1

To increase the number of sources with Very Long Baseline Interferometry (VLBI) astrometry available for comparison with the Gaia results, we have observed 31 young stars with rece…

astro-ph.SR2024★ 1 cited

Comparison of the disk precession models with the photometric behavior of TT Ari in 2021-2023

V. F. Suleimanov, K. V. Belyakov, J. M. Perales +1

We present a comparative analysis of photometric observations of the cataclysmic variable TT Ari in its bright state, obtained by the TESS orbital observatory in 2021 and 2023 and…

eess.SY2022★ 7 cited

Systems Theoretic Process Analysis of a Run Time Assured Neural Network Control System

Kerianne L. Hobbs, Benjamin K. Heiner, Lillian Busse +4

This research considers the problem of identifying safety constraints and developing Run Time Assurance (RTA) for Deep Reinforcement Learning (RL) Tactical Autopilots that use neur…

cs.LG2022★ 6 cited

Ablation Study of How Run Time Assurance Impacts the Training and Performance of Reinforcement Learning Agents

Nathaniel Hamilton, Kyle Dunlap, Taylor T Johnson +1

Reinforcement Learning (RL) has become an increasingly important research area as the success of machine learning algorithms and methods grows. To combat the safety concerns surrou…

cs.LG2022★ 1 cited

Indecision Trees: Learning Argument-Based Reasoning under Quantified Uncertainty

Jonathan S. Kent, David H. Menager

Using Machine Learning systems in the real world can often be problematic, with inexplicable black-box models, the assumed certainty of imperfect measurements, or providing a singl…