Results 31 to 40 of about 5,586 (174)
Mean‐Variance Payoff Applied to Stackelberg Games
Mathematical Methods in the Applied Sciences, EarlyView.ABSTRACT We analyse a Stackelberg duopoly in which the leader faces uncertainty about the intercept demand, while the follower observes the realised demand and decides whether to enter the market after the uncertainty is resolved. The leader evaluates the uncertainty by maximising a mean‐variance utility function that captures its risk aversion.
João M. Silva +3 more
wiley +1 more source
, 2012 This paper reports on the development of a multi–agent approach to long-term information collection in networks of energy harvesting wireless sensors.
Jennings, Nick +2 more
core +1 more source
Selective Reviews of Bandit Problems in AI via a Statistical View
MathematicsReinforcement Learning (RL) is a widely researched area in artificial intelligence that focuses on teaching agents decision-making through interactions with their environment.
Pengjie Zhou, Haoyu Wei, Huiming Zhang
doaj +1 more source
Computational Modeling of Decision Making Enhances the Adversity Researcher's Toolbox
Topics in Cognitive Science, EarlyView.Abstract Over the past decades, there has been major progress in our understanding of how adversity influences cognitive abilities and strategies. However, most of this research is based on raw performance, such as response times and accuracy. These measures are informative about decision‐making outcomes but tell us little about cognitive processes. In
Stefan Vermeent +2 more
wiley +1 more source
Indexability and index heuristics for a simple class of inventory routing problems [PDF]
, 2009 We utilise and develop Whittle's restless bandit formulation to analyse a simple class of inventory routing problems with direct deliveries. These routing problems arise from the practice of vendor-managed inventory replenishment and concern the optimal ...
Archibald, T.; id_orcid +5 more
core +1 more source
Sensors, 2023 In the Internet of Things (IoT), Low-Power Wide-Area Networks (LPWANs) are designed to provide low energy consumption while maintaining a long communications’ range for End Devices (EDs).
Benyamin Teymuri +3 more
doaj +1 more source
International Journal of Imaging Systems and Technology, Volume 36, Issue 4, July 2026.ABSTRACT Gliomas are aggressive brain tumors that require accurate imaging‐based diagnosis, where automated segmentation plays a central role in assessing tumor morphology and guiding treatment decisions. Manual delineation of gliomas is time‐consuming and prone to variability, motivating the use of deep learning to improve consistency and alleviate ...
Cecilia Diana‐Albelda +4 more
wiley +1 more source
Comparison of Video Recommendation Effects of Etc, Ucb, and Thompson Sampling Algorithms on Short-Video Platforms [PDF]
ITM Web of ConferencesThis paper comprehensively compares the performance of three multi-armed bandit (MAB) algorithms, Epsilon-Then-Commit (ETC), upper confidence bound (UCB), and Thompson sampling (TS), for video recommendation in dynamic environments.
Li Shouchuan
doaj +1 more source
Disasters, Volume 50, Issue 3, July 2026.Abstract Are social networks the key to understanding resilience in conflict? Recent studies suggest so, but relational research in conflict‐affected areas is rare. What exists stresses the importance of small circles of close family members, trusted friends, and co‐ethnic persons/groups, but tends to overlook their aggregate effect.
Solange G. Fontana
wiley +1 more source
A Survey for Deep Reinforcement Learning Based Network Intrusion Detection
Applied AI Letters, Volume 7, Issue 2, June 2026.This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang +3 more
wiley +1 more source