Results 71 to 80 of about 13,567 (273)

Non-Stationary Semi-Markov Decision Processes on a Finite Horizon

, 2012
We introduce and study a class of non-stationary semi-Markov decision processes on a finite horizon. By constructing an equivalent Markov decision process, we establish the existence of a piecewise open loop relaxed control which is optimal for the ...
Ghosh, Mrinal K, Saha, Subhamay
core   +1 more source

Both density‐ and frequency‐dependent effects determine plant growth in a dune heath ecosystem

Oikos, EarlyView.
We tested the hypothesis that both density‐ and frequency‐dependent interactions play important roles in determining plant growth in a dune heath ecosystem at several levels of available nitrogen. Plant growth was measured using the pin‐point method in a five‐block experiment with four nitrogen levels.
Christian Damgaard, Mathias Emil Kaae, Jacob Weiner, Jesper Leth Bak   +3 more
wiley   +1 more source

On A Markov Game with Incomplete Information [PDF]

We consider an example of a Markov game with lack of information on one side, that was first introduced by Renault (2002). We compute both the value and optimal strategies for a range of parameter values.
Dinah Rosenberg, Johannes Horner, Eilon Solan, Nicolas Vieille   +3 more
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Nonstationary Continuous Time Markov Decision Processes in a Semi-Markov Environment with Discounted Criterion

, 1995
This paper deals with the nonstationary continuous time Markov decision process in a semi-Markov environment with discounted criterion. The model can describe a system that itself can be modeled by a countable state nonstationary continuous time Markov ...
Hu, Q.Y.
core   +1 more source

Value passing for Communicating Piecewise Deterministic Markov Processes [PDF]

, 2006
In this paper we extend the CPDP model, which is used for compositional specification of PDP-type stochastic hybrid systems, to the value passing CPDP model.
Strubbe, Stefan, Stefan Strubbe, Arjan Van Der Schaft, Julius, Agung, Schaft, Arjan van der; id_orcid, A. van der Schaft, S. Strubbe, Julius, Agung,, Strubbe, Stefan,, Schaft, Arjan van der,, Schaft, Arjan van der, A. Julius, Agung Julius   +12 more
core   +1 more source

Bridging Human and Plant Adaptations for Climate Resilience

PLANTS, PEOPLE, PLANET, EarlyView.
Climate change is transforming agriculture through both gradual shifts and increasingly unpredictable extremes, challenging farmers' ability to protect crops and livelihoods. This study brings together farmer experiences and plant adaptation strategies to explore how people and plants respond to similar climate pressures.
Nicola Favretto, Heng Lim Tan, Gemma Brain, Daphne Ezer   +3 more
wiley   +1 more source

Modelling the purchase dynamics of insurance customers using Markov chains

, 2005
This paper considers how various types of Markov chains can be used to help forecast the purchase behaviour of customers. The models are used in a case study of the purchase behaviour of the customers of a major insurance company.
Thomas, Lyn C., Thomas, Stephen, Bozzetto, Jean-Francois, Tang, Leilei   +3 more
core  

Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma

CPT: Pharmacometrics &Systems Pharmacology, Volume 14, Issue 3, Page 540-550, March 2025.
ABSTRACT We employed a mechanistic learning approach, integrating on‐treatment tumor kinetics (TK) modeling with various machine learning (ML) models to address the challenge of predicting post‐progression survival (PPS)—the duration from the time of documented disease progression to death—and overall survival (OS) in Head and Neck Squamous Cell ...
Kevin Atsou, Anne Auperin, Jôel Guigay, Sébastien Salas, Sebastien Benzekry   +4 more
wiley   +1 more source

IEEE TRANSACTIONS ON AUTOMATIC CONTROL, VOL. 42, NO. 12, DECEMBER 1997 1663 The Policy Iteration Algorithm for Average Reward

, 2007
The average cost optimal control problem is addressed for Markov decision processes with unbounded cost. It is found that the policy iteration algorithm generates a sequence of policies which are (a strong stability condition), where c is the cost ...
Markov Decision Processes
core  

Redefining Optimal Coverage Path Planning for FLS‐Equipped AUVs With Deep Reinforcement Learning

Journal of Field Robotics, EarlyView.
ABSTRACT Autonomous Underwater Vehicles (AUVs) have emerged as indispensable tools for a variety of subsea tasks, from habitat monitoring and seabed mapping to infrastructure inspection and mine countermeasures. A fundamental challenge in this field is Coverage Path Planning (CPP), the problem of ensuring complete and efficient area coverage.
Lorenzo Cecchi, Alberto Topini, Alessandro Bucci, Alessandro Ridolfi   +3 more
wiley   +1 more source