Proposing a novel optimized charging #schedulingframework for supporting multiple EVs: “Optimal Charge Scheduling and Navigation for Multiple #EV Using #DeepReinforcementLearning and #WhaleOptimization” by Aby N Raj, Sakthivel K. ACSIS Vol. 40 p. 55–60; tinyurl.com/m2vsmewn

📢 #highlycited paper 📚 Integration of #DeepReinforcementLearning with Collaborative Filtering for Movie #RecommendationSystems 🔗 mdpi.com/2076-3417/14/3… 👨‍🔬 by Sony Peng et al. 🏫 Soonchunhyang University #coldstart #collaborativefilteringHi3EV7

☀️ Welcome to read these highlycited papers in the Section "Computing and Artificial Intelligence"! 1. A #DeepReinforcementLearning-Based Algorithm for Multi-Objective Agricultural Site Selection and Logistics Optimization Problem mdpi.com/2076-3417/14/1… by Huan Liu, Jizhe Zhang, Zhao Zhou, Yongqiang Dai and Lijing Qin 2. Somersault Foraging and Elite Opposition-Based Learning #DungBeetleOptimization Algorithm mdpi.com/2076-3417/14/1… by Daming Zhang, Zijian Wang and Fangjin Sun 3. CL-YOLOv8: #CrackDetection Algorithm for Fair-Faced Walls Based on Deep Learning mdpi.com/2076-3417/14/2… by Qinjun Li, Guoyu Zhang and Ping Yang 4. #EmotionRecognition in Usability Testing: A Framework for Improving Web Application UI Design mdpi.com/2076-3417/14/1… by Darius Drungilas, Ignas Ramašauskas and Mindaugas Kurmis 5. Fabric #DefectDetection Based on Improved Lightweight YOLOv8n mdpi.com/2076-3417/14/1… by Shuangbao Ma, Yuna Liu and Yapeng Zhang

🤖📍 Join us for a new #ModellingSeminar! 📖 Efficient & generalizable DRL: Sim-to-Real + semantic integration 🎤 Lucía Güitta López 📆 Wed 18 Feb | 12:30 CET 📍 Rey Francisco 4 (5th floor) #DeepReinforcementLearning #Sim2Real #Robotics #AI

In "A Comprehensive Survey on Self-Interpretable Neural Networks", @hkust, @NUAA_official, and @UCAS1978 authors review five #SINN approaches, attribution-, function-, concept-, prototype-, and rule-based, examined across image, text, graph data and #DeepReinforcementLearning.

Reinforcement Learning Course This course teaches you practical reinforcement learning through hands-on implementation of Deep RL algorithms. 📚 Theory + Hands on Projects + Challenge 🔗 Course Link github.com/huggingface/de… #DeepReinforcementLearning #DeepLearning

📈Highly Cited Paper on #mdpisystems Reinforcement Learning-Based Multi-Objective Optimization for Generation Scheduling in Power Systems brnw.ch/21wZ8fQ by authors from Pukyong National University #PowerSystems #DeepReinforcementLearning #EconomicDispatchs

IA2 uses Deep Reinforcement Learning to slash database runtimes by 40%, while new Hyperbolic SVM techniques utilize semidefinite relaxation. - hackernoon.com/ai-driven-data… #deepreinforcementlearning #databaseindexoptimization

IA2 revolutionizes index selection with rapid training, reducing SQL runtime by 61% via adaptive action pruning and workload modeling - hackernoon.com/adaptive-actio… #deepreinforcementlearning #databaseperformanceai

IA2 uses a two-phase framework to generate states and action pools from workloads, enabling RL agents to make sequential index selection decisions. - hackernoon.com/unseen-workloa… #deepreinforcementlearning #ia2systemframework

BREAKING: Open-source AI trading bot, leveraging Deep Reinforcement Learning like AlphaGo, aims for 80-120% annual returns in XAUUSD. #AlgorithmicTrading #DeepReinforcementLearning

The TD3-TD-SWAR model advances database optimization by framing index selection as a DRL problem with adaptive action masking for faster training. - hackernoon.com/adaptive-actio… #deepreinforcementlearning #td3tdswarmodel

From Anywhere to the Destination: Visual Reinforcement Learning for GNSS-Denied Drone Navigation jcst.ict.ac.cn/article/doi/10… #DeepReinforcementLearning #DroneNavigation #VisionForRobotics #AutonomousDriving @ZJU_China

Read #Paper "Locally Centralized Execution for Less Redundant Computation in Multi-Agent Cooperation" by Yidong Bai and Toshiharu Sugawara. See more details at: doi.org/10.3390/info15… #MultiAgent #DeepReinforcementLearning #AI #Cooperation @ComSciMath_Mdpi

Check this newly published article "Self-Adapting CPU Scheduling for Mixed Database Workloads via Hierarchical #DeepReinforcementLearning" at brnw.ch/21wXEpT Authors: Suchuan Xing, Yihan Wang and Wenhe Liu #mdpisymmetry #databasesystems @DukeU @Penn @CarnegieMellon

Daniel Fuertes presented NaviFormer at #IROS2025: a model based on #DeepReinforcementLearning and #Transformers to holistically solve the robot navigation problem. short.upm.es/0yzwq #Robotics #AI #Innovation #Research @La_UPM @telecoupm @IROS2025