Results 71 to 80 of about 112,777 (296)
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
Variance Swap Pricing under Markov-Modulated Jump-Diffusion Model
This paper investigates the pricing of discretely sampled variance swaps under a Markov regime-switching jump-diffusion model. The jump diffusion, as well as other parameters of the underlying stock’s dynamics, is modulated by a Markov chain representing
Shican Liu +3 more
doaj +1 more source
Economists continue to debate the importance of nonlinearity to their discipline. When it comes to forecasting levels, unit roots seems to be quite prevalent, and there has been a great deal of skepticism about nonlinear models. See the arguments pro and con in Ramsey (1996).
Mizrach, Bruce, Watkins, James
openaire +2 more sources
Adaptive Macroscopic Ensemble Allocation for Robot Teams Monitoring Spatiotemporal Processes
We propose an online, environment feedback‐driven macroscopic ensemble approach to adapt robot team task allocation in spatiotemporal environments by controlling robot populations rather than assigning individual robots, all while maintaining robust team performance even for small teams. Our simulation and experimental results show better or comparable
Victoria Edwards +2 more
wiley +1 more source
Consensus for Multiple Unmanned Surface Vehicle (Musv) Systems with Markov Switching Topologies
This paper is concerned with sampled-data leader following consensus of multiple unmanned surface vehicle (MUSV) systems with random switching network topologies and wave-induced disturbance.
Wang Liyuan, Yue Wei, Zhang Rubo
doaj +1 more source
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source
Modelling foreign exchange rates: a comparison between markov-switching and markov-switching GARCH
Foreign exchange rate is important as it determines a country's economic condition. It is used to carry out transfers of purchasing power between two or more countries. Volatility in exchange rates may result in difficulty in decision making especially, in financial sectors as high volatility could increase the risk in exchange rates.
Mohd Azizi Amin Nunian +2 more
openaire +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
Levy Approximation of Impulsive Recurrent Process with Semi-Markov Switching [PDF]
In this paper, the weak convergence of impulsive recurrent process with semi-Markov switching in the scheme of Levy approximation is proved. Singular perturbation problem for the compensating operator of the extended Markov renewal process is used to ...
Koroliuk, V. S. +2 more
core
Introduction In recent years, the treatment of spinal muscular atrophy (SMA), a rare disease, has significantly progressed, improving patients' survival and overall quality of life. However, current SMA treatments are expensive, and some (nusinersen) are very inconvenient for patients.
Andrej Belančić +4 more
wiley +1 more source

