Results 11 to 20 of about 731,139 (136)

Analysis of methods for simulating character encounters in a game with RPG elements

Journal of Computer Sciences Institute
This 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   +2 more sources

On the Nash Equilibria of a Simple Discounted Duel [PDF]

Operations Research and Decisions, 2023
We formulate and study a two-player – duel – game as a nonzero-sum discounted stochastic game. Players P1, and P2 are standing in place and, in each turn, one or both may shoot at the other player. If Pn shoots at Pm (m ≠ n), either he hits and kills him
A. Kehagias
semanticscholar   +1 more source

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

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, Alberto Acuto, Yihang Zhou, Dominik Wojtczak   +3 more
wiley   +1 more source

Optimizing Electric Vehicle Charging Scheduling With Deep Q Networks and Long Short‐Term Memory‐Based Electricity and Battery State of Charge Prediction

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, Subhasish Deb, Kshetrimayum Robert Singh, Subir Datta, Ahmet Onen, Taha Selim Ustun, Jaesung Jung   +6 more
wiley   +1 more source

Multiobjective Environmental Cleanup with Autonomous Surface Vehicle Fleets Using Multitask Multiagent Deep Reinforcement Learning

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, Samuel Yanes, Manuel Perales, Daniel Gutiérrez, Sergio Toral   +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, Li Zhang, Qihang Jiao, Samuel Krain   +3 more
wiley   +1 more source

Signal Timing and CAV Trajectory Joint Control Under Mixed Vehicular Environments With Hierarchical Proximal Policy Optimisation

IET Intelligent Transport Systems, Volume 20, Issue 1, January/December 2026.
This paper introduces SVCC‐HPPO, a novel Signal‐Vehicle Cooperative Control framework using an improved Hierarchical Proximal Policy Optimisation (H‐PPO) algorithm to jointly optimise traffic signal timing and Connected/Autonomous Vehicle (CAV) trajectories in mixed traffic environments.
Zongyuan Wu, Decai Wang, Mengxin Qiu, Gen Li, Wenxuan Li, Yadan Yan   +5 more
wiley   +1 more source

A Survey: Energy Optimisation Approaches in Urban Rail Systems (AI‐Based and Non‐AI‐Based)

IET Intelligent Transport Systems, Volume 20, Issue 1, January/December 2026.
This article presents a systematic review of energy optimisation strategies for urban rail systems, covering speed profile, timetable, regenerative braking, energy storage and power‐supply optimisation. We synthesise methodological trends and reported energy‐saving performance across AI‐based and non‐AI approaches.
Cakra Adipura Wicaksana, Zhongbei Tian, Stuart Hillmansen   +2 more
wiley   +1 more source

Regret Minimization in Stochastic Contextual Dueling Bandits.

CoRR, 2020
Wrong result with incremental contribution, major revision ...
Saha, Aadirupa, Gopalan, Aditya
openaire   +4 more sources