Results 41 to 50 of about 1,345 (165)

Deep Reinforcement Learning Based Autonomous Decision‐Making for Cooperative Uncrewed Aerial Vehicles: A Search and Rescue Real World Application

Journal of Field Robotics, EarlyView.
ABSTRACT This paper presents the first end‐to‐end framework that combines guidance, navigation, and centralized task allocation for multiple UAVs performing autonomous search‐and‐rescue (SAR) in GNSS‐denied indoor environments. A twin delayed deep deterministic policy gradient controller is trained with an artificial potential field (APF) reward that ...
Thomas Hickling, Maxwell Hogan, Abdulla Tammam, Nabil Aouf   +3 more
wiley   +1 more source

In silico modelling of CD8 T cell immune response links genetic regulation to population dynamics

ImmunoInformatics
The CD8 T cell immune response operates at multiple temporal and spatial scales, including all the early complex biochemical and biomechanical processes, up to long term cell population behavior.In order to model this response, we devised a multiscale ...
Thi Nhu Thao Nguyen, Madge Martin, Christophe Arpin, Samuel Bernard, Olivier Gandrillon, Fabien Crauste   +5 more
doaj   +1 more source

When in Doubt, Tax More Progressively? Uncertainty and Progressive Income Taxation

International Economic Review, EarlyView.
ABSTRACT We study the optimal income tax problem under parameter uncertainty about household preferences and wage dynamics. We derive conditions characterizing how such uncertainty affects optimal tax policy. To quantify the effect, we estimate a life‐cycle model using US data and a Bayesian approach.
Minsu Chang, Chunzan Wu
wiley   +1 more source

Measure‐valued processes for energy markets

Mathematical Finance, Volume 35, Issue 2, Page 520-566, April 2025.
Abstract We introduce a framework that allows to employ (non‐negative) measure‐valued processes for energy market modeling, in particular for electricity and gas futures. Interpreting the process' spatial structure as time to maturity, we show how the Heath–Jarrow–Morton approach can be translated to this framework, thus guaranteeing arbitrage free ...
Christa Cuchiero, Luca Di Persio, Francesco Guida, Sara Svaluto‐Ferro   +3 more
wiley   +1 more source

Numerical method for optimal stopping of piecewise deterministic Markov Processes

, 2009
In this talk, the optimal stopping problem of piecewise-deterministic Markov processes is studied. Such processes consist of a mixture of deterministic motion and random jumps.
de Saporta, Benoîte, Dufour, François
core   +2 more sources

Piecewise deterministic Markov processes for continuous-time Monte Carlo [PDF]

, 2018
\ua9 2018, Institute of Mathematical Statistics.Recently, there have been conceptually new developments in Monte Carlo methods through the introduction of new MCMC and sequential Monte Carlo (SMC) algorithms which are based on continuous-time, rather ...
Fearnhead P, Pollock M, Bierkens J, Roberts GO   +3 more
core   +3 more sources

Reinforcement Learning for Jump‐Diffusions, With Financial Applications

Mathematical Finance, EarlyView.
ABSTRACT We study continuous‐time reinforcement learning (RL) for stochastic control in which system dynamics are governed by jump‐diffusion processes. We formulate an entropy‐regularized exploratory control problem with stochastic policies to capture the exploration–exploitation balance essential for RL.
Xuefeng Gao, Lingfei Li, Xun Yu Zhou
wiley   +1 more source

Navigating Supply Shocks: Sector Resilience and Production Prices Through Stochastic Input–Output Modeling

Mathematical Finance, EarlyView.
ABSTRACT This study develops a novel multivariate stochastic framework for assessing systemic risks, such as climate and nature‐related shocks, within production or financial networks. By embedding a linear stochastic fluid network, interpretable as a generalized vector Ornstein–Uhlenbeck process, into the production network of interdependent ...
Giovanni Amici, Gianluca Fusai, Anna Maria Gambaro, Daniele Marazzina   +3 more
wiley   +1 more source

Bayesian Inference for Multivariate Monotone Densities

Scandinavian Journal of Statistics, EarlyView.
ABSTRACT We consider a nonparametric Bayesian approach to estimation and testing for a multivariate monotone density. Instead of following the conventional Bayesian approach of imposing a prior that satisfies the monotonicity restriction, we place a prior on the step heights via binning and a Dirichlet distribution. The resulting posterior distribution
Kang Wang, Subhashis Ghosal
wiley   +1 more source

Cost Optimization in a GI/M/2/N Queue with Heterogeneous Servers, Working Vacations, and Impatient Customers via the Bat Algorithm

Mathematics
This paper analyzes a finite-capacity GI/M/2/N queue with two heterogeneous servers operating under a multiple working-vacation policy, Bernoulli feedback, and customer impatience.
Abdelhak Guendouzi, Salim Bouzebda
doaj   +1 more source