An intelligent human–unmanned aerial vehicle interaction approach in real time based on machine learning using wearable gloves
T Müezzinoğlu, M Karaköse - Sensors, 2021 - mdpi.com
The interactions between humans and unmanned aerial vehicles (UAVs), whose
applications are increasing in the civilian field rather than for military purposes, are a …
applications are increasing in the civilian field rather than for military purposes, are a …
Machine-learning-based self-tunable design of approximate computing
Approximate computing (AC) is an emerging computing paradigm suitable for intrinsic error-
tolerant applications to reduce energy consumption and execution time. Different …
tolerant applications to reduce energy consumption and execution time. Different …
Programmatic strategy synthesis: Resolving nondeterminism in probabilistic programs
We consider imperative programs that involve both randomization and pure
nondeterminism. The central question is how to find a strategy resolving the pure …
nondeterminism. The central question is how to find a strategy resolving the pure …
Safety verification of decision-tree policies in continuous time
Decision trees have gained popularity as interpretable surrogate models for learning-based
control policies. However, providing safety guarantees for systems controlled by decision …
control policies. However, providing safety guarantees for systems controlled by decision …
[HTML][HTML] Correctness-guaranteed strategy synthesis and compression for multi-agent autonomous systems
Planning is a critical function of multi-agent autonomous systems, which includes path
finding and task scheduling. Exhaustive search-based methods such as model checking …
finding and task scheduling. Exhaustive search-based methods such as model checking …
Spectral analysis and Bi-LSTM deep network-based approach in detection of mild cognitive impairment from electroencephalography signals
A Said, H Göker - Cognitive Neurodynamics, 2024 - Springer
Mild cognitive impairment (MCI) is a neuropsychological syndrome that is characterized by
cognitive impairments. It typically affects adults 60 years of age and older. It is a noticeable …
cognitive impairments. It typically affects adults 60 years of age and older. It is a noticeable …
Optimal decision tree policies for Markov decision processes
Interpretability of reinforcement learning policies is essential for many real-world tasks but
learning such interpretable policies is a hard problem. Particularly rule-based policies such …
learning such interpretable policies is a hard problem. Particularly rule-based policies such …
Algebraically explainable controllers: decision trees and support vector machines join forces
Recently, decision trees (DT) have been used as an explainable representation of
controllers (aka strategies, policies, schedulers). Although they are often very efficient and …
controllers (aka strategies, policies, schedulers). Although they are often very efficient and …
Analyzing intentional behavior in autonomous agents under uncertainty
Principled accountability for autonomous decision-making in uncertain environments
requires distinguishing intentional outcomes from negligent designs from actual accidents …
requires distinguishing intentional outcomes from negligent designs from actual accidents …
Quantitative analysis of configurable and reconfigurable systems
C Dubslaff - 2022 - tud.qucosa.de
Abstract (EN) The often huge configuration spaces of modern software systems render the
detection, prediction, and explanation of defects and inadvertent behaviors challenging …
detection, prediction, and explanation of defects and inadvertent behaviors challenging …