reinforcement learning

Reinforcement Learning Driven Logic Synthesis

Hierarchical joint optimization of traffic signals and vehicle trajectories at intersections via deep reinforcement learning

Robust Trading Strategies Through Topological Features and Deep Reinforcement Learning

Adaptive intelligent resource optimization in wireless sensor networks using reinforcement learning and compressive sensing

In response to the energy and memory limitations of WSNs, this research work introduces a new approach: EMPIRE-CS (Energy and Memory-optimized Performance with Iterative Reinforcement and Compressive Sensing). It is a hybrid approach combining compressive sensing with reinforcement learning and game-theoretic cluster...

Artificial Intelligence in Electronic Design Automation: A Survey on Logic Synthesis and Netlist Optimization

Modern digital integrated circuits contain very large numbers of logic gates, and the conventional heuristics used in logic synthesis and netlist optimization struggle to explore the resulting design space efficiently. Artificial Intelligence (AI) and Machine Learning (ML) have therefore been investigated as complement...

pv-residual-rl: network-aware rooftop PV subsidy planning with an exact allocation layer and residual reinforcement learning

Simulator, baselines, experiment scripts, per-scenario results and trained models for the multi-year allocation of a rooftop-PV subsidy budget across the 32 neighbourhoods of an IEEE 33-bus feeder under uncertain acceptance, demand growth and irradiance (19 years of PVGIS data for Tehran). The package contains the LinD...

CTAM-RL: Continual Threat-Aware Memory for Continual Reinforcement Learning in Autonomous Cyber Defense

{ "upload_type": "software", "title": "CTAM-RL: Continual Threat-Aware Memory for Continual Reinforcement Learning in Autonomous Cyber Defense (v1.1.0)", "description": "Code, extracted attack profiles, and per-seed results for the manuscript 'A Continual Reinforcement Learning Framework for Autonomous Cyber Defense Un...

Project TALOS: Tactical Agentic Literature Orchestration System

Project TALOS is an autonomous research intelligence platform powered by deep reinforcement learning (DDDQN), multi-tier LLM orchestration, and the Grey Wolf Optimizer (GWO). It conducts end-to-end scientific literature discovery and evaluation across 18 academic APIs.

Application of Machine Learning in the Context of Bioenergy

"CyberWarEnv2102026 Reproducible Registry — 160 Training Runs (EXP-2026-000001..000010)"

n=20، 160 runs SHA-256 verified، v2.1.0 ✅ License: CC-BY-4.0 ✅ Version: v2.1.0 ✅ Resource type: Dataset ✅ Keywords: reinforcement learning, cyber defense, reproducibility, PPO, DQN

An AI-Assisted Approach to Arithmetic Logic Unit (ALU) Design Optimization for Enhanced Processor Performance and Efficiency

This research explores how Artificial Intelligence can enhance the optimization of Arithmetic Logic Units (ALUs), which are crucial for processor speed, energy efficiency, and silicon area. Traditional ALU design relies on fixed architectures and rule-based heuristics, but the proposed framework integrates Graph Neural...

Artificial Intelligence-Assisted Design for Enhanced Performance and Energy Efficiency in Computer Architecture

This research journal discusses how Artificial Intelligence (AI) and Machine Learning (ML) can enhance computer architecture design by addressing challenges in performance and energy efficiency. Traditional methods rely on expert intuition and exhaustive simulations, which are limited when exploring vast design spaces....