Results 21 to 30 of about 270 (146)
Fusing Reward and Dueling Feedback in Stochastic Bandits [PDF]
CoRRThis paper investigates the fusion of absolute (reward) and relative (dueling) feedback in stochastic bandits, where both feedback types are gathered in each decision round. We derive a regret lower bound, demonstrating that an efficient algorithm may incur only the smaller among the reward and dueling-based regret for each individual arm.
Xuchuang Wang +6 more
openalex +4 more sources
Regret Minimization in Stochastic Contextual Dueling Bandits [PDF]
CoRR, 2020 Wrong result with incremental contribution, major revision ...
Aadirupa Saha, Aditya Gopalan
+6 more sources
Robust Pairwise n-Person Stochastic Duel Game [PDF]
Mathematics, 2021 Song-Kyoo Kim, Kim Song-Kyoo
exaly +2 more sources
The effect of ammunition supplying times on stochastic duels
Metrika, 2012 This paper studies a duel model by incorporating the idea of correlated fire assuming that the duelists possess two types of weapon differing in firing rates and single short kill probabilities. General result for the win probabilities obtained have been illustrated for the case when the interfiring times follow exponential distribution.
Yaofeng Ren, Chuanzhi Feng
openalex +2 more sources
Speed Bump and Stock Market Quality: Evidence From NYSE American
Financial Management, EarlyView.ABSTRACT Should trading speed of high‐frequency traders be regulated? Using the data from the New York Stock Exchange American, this paper examines the impact of a speed bump on market liquidity and price discovery. Our results indicate that the use of a speed bump can lower the costs of adverse selection through reducing informed trading.
Bo Liu, Ke Xu
wiley +1 more source
Analysis of methods for simulating character encounters in a game with RPG elements
Journal of Computer Sciences InstituteThis paper investigates algorithms that predict the outcome of a duel in a game with RPG elements and determine the losses incurred. The aim is to evaluate the effectiveness of the following approaches: based on Lanchester's laws and stochastic, using ...
Michał Zdybel, Jakub Smołka
doaj +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
Energy Science &Engineering, Volume 14, Issue 5, Page 2583-2599, May 2026.Schematic diagram showing the proposed approach for EV charging/discharging. ABSTRACT The number of electric vehicles (EVs) on the road is rising as a result of recent advancements in EV technology, and EVs are important to the smart grid economy. Demand response schemes involving electric vehicles have the potential to dramatically reduce the cost of ...
F. Zonuntluanga +6 more
wiley +1 more source
Advanced Intelligent Systems, Volume 8, Issue 2, February 2026.This study presents a multitask strategy for plastic cleanup with autonomous surface vehicles, combining exploration and cleaning phases. A two‐headed Deep Q‐Network shared by all agents is traineded via multiobjective reinforcement learning, producing a Pareto front of trade‐offs.
Dame Seck +4 more
wiley +1 more source
Adaptive Satellite Selection via Deep Reinforcement Learning for Dynamic Emergency Scenarios
IET Communications, Volume 20, Issue 1, January/December 2026.This work proposes a reinforcement learning–based satellite handover framework designed for emergency communication scenarios. The method adaptively responds to bandwidth and CNR fluctuations, achieving improved link stability under both deterministic and stochastic disturbances.
Ke Chen +3 more
wiley +1 more source