Results 221 to 230 of about 235,639 (329)

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source

Dynamic Bayesian Network Modeling of the Interplay between EGFR and Hedgehog Signaling. [PDF]

PLoS One, 2015
Fröhlich H, Bahamondez G, Götschel F, Korf U.   +3 more
europepmc   +1 more source

Enabling Stochastic Dynamic Games for Robotic Swarms

Advanced Intelligent Systems, EarlyView.
This paper scales stochastic dynamic games to large swarms of robots through selective agent modeling and variable partial belief space planning. We formulate these games using a belief space variant of iterative Linear Quadratic Gaussian (iLQG). We scale to teams of 50 agents through selective modeling based on the estimated influence of agents ...
Kamran Vakil, Alyssa Pierson
wiley   +1 more source

Multi-Target Tracking of Human Spermatozoa in Phase-Contrast Microscopy Image Sequences using a Hybrid Dynamic Bayesian Network. [PDF]

Sci Rep, 2018
Arasteh A, Vosoughi Vahdat B, Salman Yazdi R.   +2 more
europepmc   +1 more source

MusicSwarm: Biologically Inspired Intelligence for Music Composition

Advanced Intelligent Systems, EarlyView.
Biologically inspired swarms of frozen foundation models self‐organize to compose complex music without fine‐tuning. By coordinating through stigmergic signals, decentralized agents dynamically evolve specialized roles and adapt to solve complex tasks.
Markus J. Buehler
wiley   +1 more source

Improved brain effective connectivity modelling by dynamic Bayesian networks

İlkay Ulusoy, Salih Geduk
openalex   +2 more sources

Artificial Intelligence in Autonomous Mobile Robot Navigation: From Classical Approaches to Intelligent Adaptation

Advanced Intelligent Systems, EarlyView.
Artificial intelligence (AI) is reshaping autonomous mobile robot navigation beyond classical pipelines. This review analyzes how AI techniques are integrated into core navigation tasks, including path planning and control, localization and mapping, perception, and context‐aware decision‐making. Learning‐based, probabilistic, and soft‐computing methods
Giovanna Guaragnella, Angelo Cardellicchio, Cosimo Patruno, Massimiliano Nitti, Nicola Pedrocchi, Vito Renò   +5 more
wiley   +1 more source

Learning and Policy Search in Stochastic Dynamical Systems with Bayesian\n Neural Networks [PDF]

, 2016
Stefan Depeweg, José Miguel Hernández-Lobato, Finale Doshi‐Velez, Steffen Udluft   +3 more
openalex   +1 more source

Towards Advanced Intelligent and Perceptive Soft Grippers

Advanced Intelligent Systems, EarlyView.
Implementing soft yet strong and intelligent soft grippers request innovative and creative solutions in designing soft bodies and seamlessly integrating actuated systems with hierarchical sensing. This review systematically analyses soft grippers with a deep understanding of core components, from fundamental design principles to actuation and sensing ...
Haneul Kim, Hayeon Shin, Seik Park, Changbeom Shim, Seonggun Joe   +4 more
wiley   +1 more source

Disentangling Aleatoric and Epistemic Uncertainty in Physics‐Informed Neural Networks: Application to Insulation Material Degradation Prognostics

Advanced Intelligent Systems, EarlyView.
Physics‐Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ) capabilities.
Ibai Ramirez, Jokin Alcibar, Joel Pino, Mikel Sanz, Jose I. Aizpurua   +4 more
wiley   +1 more source