reinforcement learning

Scalable Multi-UAV Target Assignment via Permutation-Invariant Reinforcement Learning and Conditional Control-Barrier-Function Safety Filtering

Coordinating multiple unmanned aerial vehicles (UAVs) to assign targets and generate collision-free trajectories in dynamic, obstacle-dense environments is a challenging problem with applications in search-and-rescue, surveillance, and precision agriculture. Existing deep reinforcement learning approaches for joint tar...

AuditTune campaign evidence: experiment ledger, agent-written planner code, and figure-generation scripts for auditable policy adjustment in reinforcement learning control

Evidence package for the manuscript "An Auditable Learning-Curve-Driven Automatic Policy Adjustment Framework for Engineering Reinforcement Learning Control Systems" (EAAI submission). The dataset contains the complete experiment ledger, the planner source code written by the diagnosis-driven agent, and the scripts tha...

Robust Autonomous Lunar Landing Under Uncertain Physics

The project studies whether training an agent across randomized environment physics can improve its performance on previously unseen conditions compared with training under fixed physics. It uses the LunarLander-v3 environment and Proximal Policy Optimization (PPO), alongside a custom PyTorch actor–critic implementatio...

A Mobile-Centric Approach to Improving the Performance of Decentralized Wireless Networks

The proliferation of wireless devices and intelligent environments has led to increasingly dense, interference-prone Wireless Local Area Network (WLAN) deployments. Recent amendments, such as IEEE 802.11ax/be, aim to enhance spatial reuse (SR) by optimizing spectrum efficiency. However, current SR initiatives face sign...

Controlled rough SDEs, pathwise stochastic control and dynamic programming principles

We study stochastic optimal control of rough stochastic differential equations (RSDEs). This is in the spirit of the pathwise control problem (Lions–Souganidis 1998, Buckdahn–Ma 2007; also Davis–Burstein 1992), with renewed interest and recent works drawing motivation from filtering, SPDEs, and reinforcement learning....

Agentic AIGC: A Survey of Visual Generation Agents

Visual generation is becoming a general component of AI infrastructure, supporting content creation across design, entertainment, education, science, and industry. Generative and multimodal models have substantially improved single-pass synthesis. At the same time, multi-step visual creation requires spatial precision,...

AETERNA Quantum Matrix Acceleration & Zero-Copy Sovereign IPC: Sub-Microsecond Lock-Free Shared Memory Ring Buffers, Aharonov-Bohm Topological Phase Protection on NVIDIA Ada Lovelace sm_89, and Zen 4 AVX-512 Concurrency

AETERNA QUANTUM MATRIX ACCELERATION & ZERO-COPY SOVEREIGN IPC: Sub-Microsecond Lock-Free Shared Memory Ring Buffers, Aharonov-Bohm Topological Phase Protection on NVIDIA Ada Lovelace sm_89, and Zen 4 AVX-512 Concurrency Author: Dimitar Stavrev Prodromov (AETERNA Technologies HQ, Pomorie, Bulgaria)Authority Signature: 0...

PIPO: Physics-informed deep reinforcement learning for pareto-optimal control for active suspension system

Stable, high-temperature acoustic sonoluminescence using learning-based control

Abstract Achieving high collapse temperatures under stable operating conditions is a central challenge in acoustic cavitation and sonoluminescence, as instabilities typically limit energy focusing. Conventional high-amplitude, low-frequency driving favors high collapse temperatures but simultaneously triggers shape ins...

Code for "Multi-criteria prioritized reinforcement learning for autonomous underwater vehicle navigation in 3D multi-node environments"

Artificial Intelligence–Driven Intrusion Detection Systems: A Systematic Review of Machine Learning, Deep Learning, and Adaptive Ensemble Approaches

This is a critical systematic review of 40 peer-reviewed articles published between 2021 and 2025 on artificial intelligence-enhanced Intrusion Detection Systems (IDS).To maintain rigour and transparency in the review, the PRISMA 2020 and Kitchenham guidelines are adhered to.The appropriate literature was also searched...

sruthijanga/EANAS-GreenAI: EANAS-GreenAI

EANAS-GreenAI v1.0.0 EANAS-GreenAI is a research implementation of Energy-Aware Neural Architecture Search for Edge-AI Deployments. It combines CNN architecture search, reinforcement learning, and evolutionary optimization to balance model accuracy, inference latency, and energy consumption. Key Features: Five-block CN...