Buscar recursos académicos

ABSTRACT Background and Aims De novo drug design is the process of generating novel lead compounds that possess desirable pharmacological activities and optimal physicochemical properties for therapeutic development. In ...

ABSTRACT This paper presents HealthNet, a novel framework for the dynamic optimisation of healthcare transportation networks using multi‐agent reinforcement learning. HealthNet leverages a spatiotemporal dependency mod...

ABSTRACT Intrinsic motivation serves as the predominant paradigm of exploration in reinforcement learning. In pursuit of an informative and robust state representation, the behavioural metric groups behaviourally equival...

ABSTRACT As a government‐regulated public service, traffic signal control (TSC) requires reliable and transparent decision‐making. However, existing deep reinforcement learning (DRL) methods, despite improvements in ...

Abstract To address the challenge of low adaptability in distribution network planning caused by significant regional differences in electricity consumption, this paper proposes a distribution network planning method bas...

ABSTRACT Efficient exploration is critical in handling sparse rewards and partial observability in deep reinforcement learning. However, most existing intrinsic reward methods based on novelty rely on single‐step obser...

ABSTRACT Adversarial jamming attacks have increased on communication systems, causing distortion and threatening transmissions. Typical attacks rely on traditional, well‐defined cryptographic protocols and frequency‐...