IEEE

Optimizing Plastic Waste Collection in Water Bodies Using Heterogeneous Autonomous Surface Vehicles With Deep Reinforcement Learning

Abstract: This letter presents a model-free deep reinforcement learning framework for informative path planning with heterogeneous fleets of autonomous surface vehicles to locate and collect plastic ...
GitHub

Scaling Agentic Reinforcement Learning with a Multi-Turn, Multi-Task Framework

For a minimal example of how to use the environment framework, refer to examples/simple-calculator. For the environment and training data used in our paper, see AgentBench FC. For reproducing the ...
IEEE

Reinforcement Learning-Based Voting for Feature Drift-Aware Intrusion Detection: An Incremental Learning Framework

Abstract: In Intrusion Detection Systems (IDS), stream data classification faces significant challenges due to concept drifts and feature evolution, where traditional methods struggle to maintain ...