Abstract: In this paper, a hierarchical smart grid architecture is presented. The concept of smart home is extended in two aspects: 1) from traditional households with smart devices, such as advanced ...

Unmanned surface vehicles (USVs) nowadays have been widely used in ocean observation missions, helping researchers to monitor climate change, collect environmental data, and observe marine ecosystem ...

To provide quantitative analysis of strategic confrontation game such as cross-border trades like tariff disputes and competitive scenarios like auction bidding, we propose an alternating Markov ...

Quantum hardware is prone to errors and quantum error correction is a fundamental technique in quantum computing. We present an automated method to synthesize ...

Implements selected inverse reinforcement learning (IRL) algorithms as part of COMP3710, supervised by Dr Mayank Daswani and Dr Marcus Hutter. My final report is available here and describes the ...

This repository contains the Python code for reproducing the decentralized QECO (QoE-Oriented Computation Offloading) algorithm, designed for Mobile Edge Computing (MEC) systems. In the realm of ...

Abstract: We consider an energy harvesting sensor transmitting latency-sensitive data over a fading channel. We aim to find the optimal transmission scheduling policy that minimizes the packet queuing ...

Reinforcement learning has witnessed recent applications to a variety of tasks in quantum programming. The underlying assumption is that those tasks could be modeled as Markov decision processes (MDPs ...

Considering the dynamics and non-linear characteristics of biped robots, gait optimization is an extremely challenging task. To tackle this issue, a parallel heterogeneous policy Deep Reinforcement ...

Deep reinforcement learning (deep RL) has the potential to replace classic robotic controllers. State-of-the-art Deep Reinforcement algorithms such as Proximal Policy Optimization, Twin Delayed Deep ...

Congestion control plays an essential role on the internet to manage overload, which affects data transmission performance. The random early detection (RED) algorithm belongs to active queue ...

Though we’re living through a time of extraordinary innovation in GPU-accelerated machine learning, the latest research papers frequently (and prominently) feature algorithms that are decades, in ...