Results 211 to 220 of about 207,453 (329)
Enabling Stochastic Dynamic Games for Robotic Swarms
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
MusicSwarm: Biologically Inspired Intelligence for Music Composition
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 (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 +5 more
wiley +1 more source
Reliability modelling and analysis of a multi-state element based on a dynamic Bayesian network
Zhiqiang Li +4 more
openalex +1 more source
Learning and Policy Search in Stochastic Dynamical Systems with Bayesian\n Neural Networks [PDF]
Stefan Depeweg +3 more
openalex +1 more source
Towards Advanced Intelligent and Perceptive Soft Grippers
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 +4 more
wiley +1 more source
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 +4 more
wiley +1 more source
BCTI: a Bayesian network-based method for revealing critical transitions in complex biological systems. [PDF]
Tong Y +6 more
europepmc +1 more source
Dissecting Pirtobrutinib Resistance in Mantle Cell Lymphoma Through Single‐Cell Multi‐Omics
ABSTRACT Pirtobrutinib (PBN), a non‐covalent BTK inhibitor, has been approved by the FDA for relapsed/refractory mantle cell lymphoma (MCL); however, resistance to PBN has been observed. To dissect the molecular dynamics driving PBN resistance, we performed integrative single‐cell multi‐omic profiling (scRNA‐seq, scATAC‐seq, and scDNA‐seq) on ...
Fangfang Yan +10 more
wiley +1 more source

