Buchumschlag

Coupled autoregressive active inference agents for control of multi-joint dynamical systems

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Nisslbeck, Tim N., Kouw, Wouter M.
Format:	Preprint
Veröffentlicht:	2024
Schlagworte:	Machine Learning Systems and Control
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Message passing-based inference in an autoregressive active inference agent
von: Kouw, Wouter M., et al.
Veröffentlicht: (2025)

Planning to avoid ambiguous states through Gaussian approximations to non-linear sensors in active inference agents
von: Kouw, Wouter M.
Veröffentlicht: (2024)

Online Bayesian system identification in multivariate autoregressive models via message passing
von: Nisslbeck, T. N., et al.
Veröffentlicht: (2025)

Curvature-aware Expected Free Energy as an Acquisition Function for Bayesian Optimization
von: Meera, Ajith Anil, et al.
Veröffentlicht: (2026)

Bayesian autoregression to optimize temporal Matérn kernel Gaussian process hyperparameters
von: Kouw, Wouter M.
Veröffentlicht: (2025)

Bayesian grey-box identification of nonlinear convection effects in heat transfer dynamics
von: Kouw, Wouter M., et al.
Veröffentlicht: (2024)

An active learning method for solving competitive multi-agent decision-making and control problems
von: Fabiani, Filippo, et al.
Veröffentlicht: (2022)

Towards safe control parameter tuning in distributed multi-agent systems
von: Tokmak, Abdullah, et al.
Veröffentlicht: (2025)

Load constrained wind farm flow control through multi-objective multi-agent reinforcement learning
von: Åstrand, Teodor, et al.
Veröffentlicht: (2026)

A system identification approach to clustering vector autoregressive time series
von: Yue, Zuogong, et al.
Veröffentlicht: (2025)

Risk-sensitive control as inference with Rényi divergence
von: Ito, Kaito, et al.
Veröffentlicht: (2024)

Tracking control of latent dynamic systems with application to spacecraft attitude control
von: Zhang, Congxi, et al.
Veröffentlicht: (2024)

Scalable spectral representations for multi-agent reinforcement learning in network MDPs
von: Ren, Zhaolin, et al.
Veröffentlicht: (2024)

Learning responsibility allocations for multi-agent interactions: A differentiable optimization approach with control barrier functions
von: Remy, Isaac, et al.
Veröffentlicht: (2024)

A semi-centralized multi-agent RL framework for efficient irrigation scheduling
von: Agyeman, Bernard T., et al.
Veröffentlicht: (2024)

SafEDMD: A Koopman-based data-driven controller design framework for nonlinear dynamical systems
von: Strässer, Robin, et al.
Veröffentlicht: (2024)

Model-free system identification of surface ships in waves via Hankel dynamic mode decomposition with control
von: Palma, Giorgio, et al.
Veröffentlicht: (2025)

Control of dynamical systems with neural networks
von: Böttcher, Lucas
Veröffentlicht: (2025)

Interpretable machine-learning for predicting molecular weight of PLA based on artificial bee colony optimization algorithm and adaptive neurofuzzy inference system
von: Masoumi, Amir Pouya, et al.
Veröffentlicht: (2025)

Suppressing unknown disturbances to dynamical systems using machine learning
von: Restrepo, Juan G., et al.
Veröffentlicht: (2023)

One-shot backpropagation for multi-step prediction in physics-based system identification -- EXTENDED VERSION
von: Donati, Cesare, et al.
Veröffentlicht: (2023)

Independent policy gradient-based reinforcement learning for economic and reliable energy management of multi-microgrid systems
von: Hu, Junkai, et al.
Veröffentlicht: (2025)

A neural network-based approach to hybrid systems identification for control
von: Fabiani, Filippo, et al.
Veröffentlicht: (2024)

What can we learn from signals and systems in a transformer? Insights for probabilistic modeling and inference architecture
von: Chang, Heng-Sheng, et al.
Veröffentlicht: (2025)

A novel ANROA based control approach for grid-tied multi-functional solar energy conversion system
von: Prasad, Dinanath, et al.
Veröffentlicht: (2024)

Suboptimality analysis of receding horizon quadratic control with unknown linear systems and its applications in learning-based control
von: Shi, Shengling, et al.
Veröffentlicht: (2023)

Reservoir computing for system identification and predictive control with limited data
von: Williams, Jan P., et al.
Veröffentlicht: (2024)

Direct transfer of optimized controllers to similar systems using dimensionless MPC
von: Hromatko, Josip Kir, et al.
Veröffentlicht: (2025)

Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method
von: Caldarelli, Edoardo, et al.
Veröffentlicht: (2024)

Efficient model predictive control for nonlinear systems modelled by deep neural networks
von: Lan, Jianglin
Veröffentlicht: (2024)

GreenLight-Gym: Reinforcement learning benchmark environment for control of greenhouse production systems
von: van Laatum, Bart, et al.
Veröffentlicht: (2024)

Learning mechanical systems from real-world data using discrete forced Lagrangian dynamics
von: Hansen, Martine Dyring, et al.
Veröffentlicht: (2025)

End-to-end guarantees for indirect data-driven control of bilinear systems with finite stochastic data
von: Chatzikiriakos, Nicolas, et al.
Veröffentlicht: (2024)

Exploiting inter-agent coupling information for efficient reinforcement learning of cooperative LQR
von: Syed, Shahbaz P Qadri, et al.
Veröffentlicht: (2025)

Operator learning for energy-efficient building ventilation control with computational fluid dynamics simulation of a real-world classroom
von: Bian, Yuexin, et al.
Veröffentlicht: (2025)

Recurrent neural network-based robust control systems with regional properties and application to MPC design
von: Ravasio, Daniele, et al.
Veröffentlicht: (2025)

Delay compensation of multi-input distinct delay nonlinear systems via neural operators
von: Bajraktari, Filip, et al.
Veröffentlicht: (2025)

Learning linear dynamical systems under convex constraints
von: Tyagi, Hemant, et al.
Veröffentlicht: (2023)

Multi-agent Multi-armed Bandits with Minimum Reward Guarantee Fairness
von: Manupriya, Piyushi, et al.
Veröffentlicht: (2025)

Approximate non-linear model predictive control with safety-augmented neural networks
von: Hose, Henrik, et al.
Veröffentlicht: (2023)