Results 121 to 130 of about 57,303 (303)

Value-At-Risk Optimal Policies for Revenue Management Problems [PDF]

open access: yes, 2010
Consider a single-leg dynamic revenue management problem with fare classes controlled by capacity in a risk-averse setting. The revenue management strategy aims at limiting the down-side risk, and in particular, value-at-risk.
Meissner, J, Koenig, M
core  

Large Language Model‐Based Chatbots in Higher Education

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci   +4 more
wiley   +1 more source

Stochastic energy management of DC photovoltaic microgrids using Markov decision process

open access: yesResults in Engineering
The increasing reliance on renewable energy sources, particularly photovoltaic (PV) systems, in off-grid applications presents a critical challenge: managing energy supply under random load behavior and intermittent resource availability.
Mohamed Aatabe   +3 more
doaj   +1 more source

Adaptive Autonomy in Microrobot Motion Control via Deep Reinforcement Learning and Path Planning Synergy

open access: yesAdvanced Intelligent Systems, EarlyView.
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi   +3 more
wiley   +1 more source

Allosteric Regulation of Photophysics and Binding in Oxazine‐macrocycle Complexes at Single‐molecule Resolution

open access: yesAngewandte Chemie, EarlyView.
This work explores the interactions between the oxazine dye ATTO655 and two macrocyclic hosts using optical (single‑molecule) spectroscopy. Although ATTO655 forms a classical inclusion complex with cucurbit[8]uril (CB8), its interaction with p‑sulfonatocalix[4]arene (sCX4) leads to the formation of dim exclusion complexes.
Siyu Lu   +7 more
wiley   +2 more sources

Safe Reinforcement Learning for Arm Manipulation with Constrained Markov Decision Process

open access: yesRobotics
In the world of human–robot coexistence, ensuring safe interactions is crucial. Traditional logic-based methods often lack the intuition required for robots, particularly in complex environments where these methods fail to account for all possible ...
Patrick Adjei   +3 more
doaj   +1 more source

Adaptive Macroscopic Ensemble Allocation for Robot Teams Monitoring Spatiotemporal Processes

open access: yesAdvanced Intelligent Systems, EarlyView.
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

Networked Markov Decision Processes With Delays

open access: yes, 2012
We consider a networked control system, where each subsystem evolves as a Markov decision process with some extra inputs from other systems. Each subsystem is coupled to its neighbors via communication links over which the signals are delayed, but are ...
S. Lall   +5 more
core   +1 more source

Optimizing 3D Bin Packing of Heterogeneous Objects Using Continuous Transformations in SE(3)

open access: yesAdvanced Intelligent Systems, EarlyView.
This article presents a method for solving the three‐dimensional bin packing problem for heterogeneous objects using continuous rigid‐body transformations in SE(3). A heuristic optimization framework combines signed‐distance functions, neural network approximations, point‐cloud bin modeling, and physics simulation to ensure feasibility and stability ...
Michele Angelini, Marco Carricato
wiley   +1 more source

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