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Browsing by Author "Chu, Kai-Fung"

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Deep reinforcement learning of passenger behavior in multimodal journey planning with proportional fairness

Chu, Kai-Fung; Guo, Weisi (Springer, 2023-07-20)

Multimodal transportation systems require an effective journey planner to allocate multiple passengers to transport operators. One example is mobility-as-a-service, a new mobility service that integrates various transport ...
Federated reinforcement learning for consumers privacy protection in Mobility-as-a-Service

Chu, Kai-Fung; Guo, Weisi (IEEE, 2024-02-13)

Mobility-as-a-Service (MaaS) offers multi-modal transport modes in a single service platform, which requires tremendous data and software support. Among various types of data, consumers' data is vulnerable to the communication ...
Multi-agent reinforcement learning-based passenger spoofing attack on Mobility-as-a-Service

Chu, Kai-Fung; Guo, Weisi (IEEE, 2024-03-19)

Cyber-physical systems, such as smart transportation, face security threats from both digital and physical realms. Recently, Mobility-as-a-Service (MaaS) has emerged as a novel transportation concept, offering passengers ...
Passenger spoofing attack for artificial Intelligence-based Mobility-as-a-Service

Chu, Kai-Fung; Guo, Weisi (IEEE, 2024-02-13)

Mobility-as-a-Service (MaaS), a new mobility service model that integrates multiple mobility providers, relies on many data processing technologies to manage multi-modal transport. Artificial Intelligence (AI) is one of ...
Privacy-preserving federated deep reinforcement learning for mobility-as-a-service

Chu, Kai-Fung; Guo, Weisi (IEEE, 2023-10-03)

Mobility-as-a-service (MaaS) is a new transport model that combines multiple transport modes in a single platform. Dynamic passenger behavior based on past experiences requires reinforcement-based optimization of MaaS ...
Rewiring complex networks to achieve cluster synchronization using graph convolution networks with reinforcement learning

Zou, Mengbang; Guo, Weisi; Chu, Kai-Fung (IEEE, 2024-06-10)

Synchronization on complex networks depends on a myriad of factors such as embedded dynamics, initial conditions, network structure, etc. Current literature simplifies analysis of cluster synchronization leveraging conditions ...

Browsing by Author "Chu, Kai-Fung"

Browsing by Author "Chu, Kai-Fung"

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