Results 81 to 90 of about 13,204,286 (295)

Evolutionary Stability of Prospect Theory Preferences [PDF]

We demonstrate that in simple 2 X 2 games (cumulative) prospect theory preferences can be evolutionarily stable, i.e. a population of players with prospect theory preferences can not be invaded by more rational players.
Marc Oliver Rieger
core  

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source

Optimal Control Based on Reinforcement Learning for Flexible High-Rise Buildings with Time-Varying Actuator Failures and Asymmetric State Constraints

Buildings
This study centers on the vibration suppression of high-rise building systems under extreme conditions, exploring a reinforcement learning (RL)-based vibration control strategy for flexible building systems with time-varying faults and asymmetric state ...
Min Li, Rui Xie
doaj   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Unified Theory of Machine Learning : A Dynamical Theory of Stability, Generalization, and Solvability

An independent reseacher from ...
openaire   +2 more sources

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

Advanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed, Samuel García Vázquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker   +6 more
wiley   +1 more source

Accurate screening of functional materials with machine-learning potential and transfer-learned regressions: Heusler alloy benchmark

npj Computational Materials
We present a machine learning-accelerated high-throughput (HTP) workflow for the discovery of functional materials. As a test case, quaternary and all-d Heusler compounds were screened for stable compounds with large magnetocrystalline anisotropy energy (
Enda Xiao, Terumasa Tadano
doaj   +1 more source

Method of Motion Planning for Digital Twin Navigation and Cutting of Shearer

Sensors
To further enhance the intelligence level of coal mining faces and achieve the autonomous derivation, learning, and optimization of shearer navigation cutting, this paper proposes the methods of shearer digital twin navigation cutting motion planning ...
Bing Miao, Shirong Ge, Yunwang Li, Yinan Guo   +3 more
doaj   +1 more source

Stabilization Learning: A Paradigm Transition Bridging Control Theory and Machine Learning

Stabilization learning is an interdisciplinary paradigm that bridges control theory and machine learning. Its core idea is to enable systems to adjust their policies under perturbations or environmental changes through real-time feedback and adaptive mechanisms.
openaire   +2 more sources

E–stability and stability of adaptive learning in models with asymmetric information [PDF]

The paper demonstrates how the E–stability principle introduced by Evans and Honkapohja [2001] can be applied to models with heterogeneous and private information in order to assess the stability of rational expectations equilibria under learning.
Maik Heinemann
core