Agent-based modeling (ABM) involves develo** models in which agents make adaptive
decisions in a changing environment. Machine-learning (ML) based inference models can …

In an internal combustion engine, a chemical reaction occurs between the oxygen in air and
hydrocarbon fuel. Engines operate at what is termed the stoichiometric air/fuel ratio when …

In this work we will report our initial investigation of how a neural network architecture could
become an efficient tool to model Proportional-Integral-Derivative controller (PID controller) …

Stock price forecasting has been mostly realized using quantitative information. However,
recent studies have demonstrated that sentiment information hidden in corporate annual …

In this paper, we propose a novel metric called MetrIntPair (Metric for Pairwise Intelligence
Comparison of Agent‐Based Systems) for comparison of two cooperative multiagent …

A computational approach combining machine learning (simulated annealing) and agent
based simulation is shown to approximate financial time series. The agent based model …

Facial expression recognition is an interesting and challenging subject in signal processing
and artificial intelligence. In this paper, a new method of facial expression recognition based …

A new fault tolerant model predictive control (FTMPC) strategy is proposed for three-phase
magnetically isotropic permanent magnet synchronous motor (PMSM) with complete loss of …

More and more our society is linked to the stability of financial markets and this stability
depends on key players like private companies, financial markets, investors, analysts …

The paper discusses the notions of explainability and interpretability when using decision
tree learning and agent based modeling to approximate financial time series. And how they …