most citedSurrogate Modeling and Explainable Artificial Intelligence for Complex Systems: A Workflow for Automated Simulation Exploration

1 citations · 2 across the 5 of their papers we have counts for

collaborators

7 papers

cs.AI2026

Sensitivity Analysis of Decision Rules in an Agent-Based Agro-Ecological Model

Benjamin Pianet, Baptiste Lesquoy, Paul Saves +4

Agent-based models are well-suited for modelling agro-ecological systems for decision-making, yet turning their simulations into actionable insight requires identifying which decis…

cs.RO2026

Continuous Online Fault Detection for Mobile Robots via Adaptive Edge Models

Jordan Levy, Nicolas Verstaevel, Vincent Talon +1

Mobile robots require robust, real-time fault detection capable of continuous adaptation on constrained edge hardware. While deep time-series models excel at unsupervised anomaly d…

cs.AI2026

Interpretable and Explainable Surrogate Modeling for Simulations: A State-of-the-Art Survey and Perspectives on Explainable AI for Decision-Making

Pramudita Satria Palar, Paul Saves, Muhammad Daffa Robani +6

The simulation of complex systems increasingly relies on sophisticated but fundamentally opaque computational black-box simulators. Surrogate models play a central role in reducing…

cs.LG2026

From Model-Based Screening to Data-Driven Surrogates: A Multi-Stage Workflow for Exploring Stochastic Agent-Based Models

Paul Saves, Matthieu Mastio, Nicolas Verstaevel +1

Systematic exploration of Agent-Based Models (ABMs) is challenged by the curse of dimensionality and their inherent stochasticity. We present a multi-stage pipeline integrating the…

cs.LG2026★ 1 cited

Analyzing Shapley Additive Explanations to Understand Anomaly Detection Algorithm Behaviors and Their Complementarity

Jordan Levy, Paul Saves, Moncef Garouani +2

Unsupervised anomaly detection is a challenging problem due to the diversity of data distributions and the lack of labels. Ensemble methods are often adopted to mitigate these chal…

cs.GT2025

Adaptive Agents in Spatial Double-Auction Markets: Modeling the Emergence of Industrial Symbiosis

Matthieu Mastio, Paul Saves, Benoit Gaudou +1

Industrial symbiosis fosters circularity by enabling firms to repurpose residual resources, yet its emergence is constrained by socio-spatial frictions that shape costs, matching o…

cs.AI2025★ 1 cited

Surrogate Modeling and Explainable Artificial Intelligence for Complex Systems: A Workflow for Automated Simulation Exploration

Paul Saves, Pramudita Satria Palar, Muhammad Daffa Robani +6

Complex systems are increasingly explored through simulation-driven engineering workflows that combine physics-based and empirical models with optimization and analytics. Despite t…