reinforcement learning

Understanding Teacher Personality and Professional Character through Integrated Psychological Theories

Although teacher personality has received considerable attention in educational and psychological research, integrated explanations of teachers’ personality and professional character remain limited. This study examines teacher personality through psychoanalytic, behaviorist, and humanistic perspectives to develop an i...

Intelligent Greenhouse Temperature Management: A Closed-Loop Perspective on Sensing, Modeling, Control, and Deployment

Greenhouse cultivation plays an important role in food security, resource-use efficiency, and sustainable agricultural development. Temperature management is particularly critical because it directly affects crop growth, yield and quality, energy consumption, and environmental control. To clarify the technological path...

PROPEL: Proactive Energy-Efficient Task Offloading at the Edge via Online Reinforcement Learning

Input Parameter Dataset for Stochastic Multi-Carrier SSCEE Scheduling with Electric-Drone Mobility

Input Parameter Dataset for Stochastic Multi-Carrier SSCEE Scheduling with Electric-Drone Mobility This dataset provides a structured numerical input specification for a stochastic multi-carrier energy scheduling benchmark incorporating carbon-emission trading (CET), renewable portfolio standards (RPS), peer-to-peer (P...

Explainable Reinforcement Learning for Intelligent Battery Management in Residential Microgrids

Analysis of scientific approaches to the formation of future foreign language teachers' competences

The purpose of the article is to analyze scholarly approaches to the issue of developing the competencies of students, and, in particular, future foreign language teachers. The following research objectives were identified: to define the concept of “teacher competence”; to clarify the classical pedagogical approaches t...

Artificial Neural Network: Architecture, Learning Algorithms, Applications and Challenges

Artificial neural networks (ANNs) are computational models inspired by the way biological nervous systems process information. Over the past eight decades they have grown from simple threshold units into deep, billion-parameter systems that underpin modern computer vision, language processing, healthcare analytics, fin...

Permanent Magnet Synchronous Magnet Motor Intelligent Parameter Estimation Using Machine Learning Based Nonlinear Control

MO-ADRL: Multi-Objective Adaptive Deep Reinforcement Learning for Intelligent Grids with High Renewable Penetration

Source code for the MO-ADRL framework: intelligent-grid simulator, Temporal Transformer forecaster, actor-critic agent with adaptive multi-objective reward weighting, prioritized experience replay and uncertainty-aware exploration, together with rule-based, PSO and GA baselines and convergence-analysis scripts.

A comparative review of machine learning and deep learning architectures for correlated colour temperature control in smart road lighting

The review provides a focused analysis of machine learning (ML) and deep learning (DL) models for managing correlated colour temperature (CCT) in adaptive road lighting systems. As urban infrastructure evolves towards smart, responsive technologies, the ability to dynamically control lighting parameters is critical for...

Business email sequences 2026: Reinforcement Learning (RL) reply-rate lift vs 4-send cap

Optimize email sequences with reinforcement learning. Discover how conditional modeling balances dynamic unsubscribe penalties against strict 4-send caps. Independent technical note mirroring the canonical version: https://mm-ais.com/blog/business-email-sequences-2026-reinforcement-learning-rl-reply-rate-lift-vs-4-send...

Real-Time Dynamic Pricing and Revenue Management in Hospitality 5.0

This chapter discusses upgrades in pricing strategies for the hospitality industry. It will analyze real-time dynamic pricing and advanced revenue management systems with reference to the framework of Hospitality 5.0. AI, IoT, and data analytics help to advance pricing strategies from basic static models to cutting-edg...