Search Results for author: Johan de Kleer

Found 9 papers, 0 papers with code

A Quantum Algorithm for Computing All Diagnoses of a Switching Circuit

no code implementations8 Sep 2022 Alexander Feldman, Johan de Kleer, Ion Matei

In this paper we provide a novel approach for computing diagnosis of switching circuits with gate-based quantum computers.

System Resilience through Health Monitoring and Reconfiguration

no code implementations30 Aug 2022 Ion Matei, Wiktor Piotrowski, Alexandre Perez, Johan de Kleer, Jorge Tierno, Wendy Mungovan, Vance Turnewitsch

The framework is based on a physics-based digital twin model and three modules tasked with real-time fault diagnosis, prognostics and reconfiguration.

Improving the Efficiency of Gradient Descent Algorithms Applied to Optimization Problems with Dynamical Constraints

no code implementations26 Aug 2022 Ion Matei, Maksym Zhenirovskyy, Johan de Kleer, John Maxwell

In our second algorithm, we use an ODE solver to reset the ODE solution, but no direct are adjoint sensitivity analysis methods are used.

AI Research Associate for Early-Stage Scientific Discovery

no code implementations2 Feb 2022 Morad Behandish, John Maxwell III, Johan de Kleer

Artificial intelligence (AI) has been increasingly applied in scientific activities for decades; however, it is still far from an insightful and trustworthy collaborator in the scientific process.

Playing Angry Birds with a Domain-Independent PDDL+ Planner

no code implementations9 Jul 2021 Wiktor Piotrowski, Roni Stern, Matthew Klenk, Alexandre Perez, Shiwali Mohan, Johan de Kleer, Jacob Le

This demo paper presents the first system for playing the popular Angry Birds game using a domain-independent planner.

Hybrid modeling: Applications in real-time diagnosis

no code implementations4 Mar 2020 Ion Matei, Johan de Kleer, Alexander Feldman, Rahul Rai, Souma Chowdhury

In this paper, we outline a novel hybrid modeling approach that combines machine learning inspired models and physics-based models to generate reduced-order models from high fidelity models.

BIG-bench Machine Learning

Design Space Exploration as Quantified Satisfaction

no code implementations7 May 2019 Alexander Feldman, Johan de Kleer, Ion Matei

We apply our method to the design of Boolean systems and discover new and more optimal classical digital and quantum circuits for common arithmetic functions such as addition and multiplication.

Combinatorial Optimization

Automated Process Planning for Hybrid Manufacturing

no code implementations18 May 2018 Morad Behandish, Saigopal Nelaturi, Johan de Kleer

A multimodal HM process plan is represented by a finite Boolean expression of AM and SM manufacturing primitives, such that the expression evaluates to an 'as-manufactured' artifact.

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