Advanced Power Converters and Learning in Diverse Robotic Innovation: A Review
This paper provides a comprehensive review of the integration of advanced power
management systems and learning techniques in the field of robotics. It identifies the critical …
management systems and learning techniques in the field of robotics. It identifies the critical …
[HTML][HTML] Probabilistic net load forecasting framework for application in distributed integrated renewable energy systems
JS Telle, A Upadhaya, P Schönfeldt, T Steens, B Hanke… - Energy Reports, 2024 - Elsevier
Integrating various sectors enhances resilience in distributed sector-integrated energy
systems. Forecasting is vital for unlocking full potential and enabling well-informed decisions …
systems. Forecasting is vital for unlocking full potential and enabling well-informed decisions …
Sequential Decision-Making under Uncertainty: A Robust MDPs review
W Ou, S Bi - arXiv preprint arXiv:2404.00940, 2024 - arxiv.org
This review paper provides an in-depth overview of the evolution and advancements in
Robust Markov Decision Processes (RMDPs), a field of paramount importance for its role in …
Robust Markov Decision Processes (RMDPs), a field of paramount importance for its role in …
Strong Simple Policies for POMDPs
The synthesis problem for partially observable Markov decision processes (POMDPs) is to
compute a policy that provably adheres to one or more specifications. Yet, the general …
compute a policy that provably adheres to one or more specifications. Yet, the general …
What Are the Odds? Improving the foundations of Statistical Model Checking
Markov decision processes (MDPs) are a fundamental model for decision making under
uncertainty. They exhibit non-deterministic choice as well as probabilistic uncertainty …
uncertainty. They exhibit non-deterministic choice as well as probabilistic uncertainty …
Tools at the Frontiers of Quantitative Verification
The analysis of formal models that include quantitative aspects such as timing or
probabilistic choices is performed by quantitative verification tools. Broad and mature tool …
probabilistic choices is performed by quantitative verification tools. Broad and mature tool …
Efficient Sensitivity Analysis for Parametric Robust Markov Chains
We provide a novel method for sensitivity analysis of parametric robust Markov chains.
These models incorporate parameters and sets of probability distributions to alleviate the …
These models incorporate parameters and sets of probability distributions to alleviate the …
Explanation Paradigms Leveraging Analytic Intuition (ExPLAIn)
In this paper, we present the envisioned style and scope of the new topic “Explanation
Paradigms Leveraging Analytic Intuition”(ExPLAIn) with the International Journal on …
Paradigms Leveraging Analytic Intuition”(ExPLAIn) with the International Journal on …
[HTML][HTML] Robust probabilistic temporal logics
M Zimmermann - Information Processing Letters, 2025 - Elsevier
Robust probabilistic temporal logics - ScienceDirect Skip to main contentSkip to article
Elsevier logo Journals & Books Help Search My account Sign in View PDF Download full …
Elsevier logo Journals & Books Help Search My account Sign in View PDF Download full …
Trustworthy explanations: Improved decision support through well-calibrated uncertainty quantification
H Löfström - 2023 - diva-portal.org
Abstract The use of Artificial Intelligence (AI) has transformed fields like disease diagnosis
and defence. Utilising sophisticated Machine Learning (ML) models, AI predicts future …
and defence. Utilising sophisticated Machine Learning (ML) models, AI predicts future …