IEEE

Multi-Agent Deep Reinforcement Learning for Dynamic Routing in MANETs Using Graph Neural Networks

Abstract: Mobile Ad Hoc Networks (MANETs) consist of decentralized wireless networks with dynamic topologies and frequent link failures which make achieving efficient routing extremely difficult.
Dot Physics on MSN

Creating animated graphs using VPython Glowscript for visualizations

Explore the power of interactive physics visualizations with animated graphs using VPython and GlowScript for dynamic simulations! This guide demonstrates how to create real-time animated graphs that ...
Dot Physics on MSN

Mastering animated graphs in GlowScript: VPython made easy

Learn how to create dynamic, animated graphs in GlowScript using VPython with ease! 📊 This step-by-step tutorial guides you through visualizing data, animating simulations, and mastering interactive ...
IEEE

Dynamic Graph-Based Deep Reinforcement Learning to V2X Channel Congestion Collaborative Control

Abstract: As an important component of intelligent transportation systems, vehicle-to-everything (V2X) provides critical communication support for road safety through real-time interactive and ...
GitHub

YAML DSL-based rule engine with AST processing, Python compilation, audit trails, and reactive APIs for dynamic business rule evaluation.

Firefly Framework Rule Engine provides a powerful business rule evaluation system based on a custom YAML DSL. Rules are defined in YAML format and parsed into an Abstract Syntax Tree (AST) for ...