## 2 Development of Seismic Resilience of Modern Urban Communities
### Research on Seismic Resilience of Modern CISs  
#### 2.2.1 Seismic Resilience of Individual CISs  
Extensive research has investigated the seismic behaviour of various modern CISs. These systems span diverse domains, including healthcare, gas, and water infrastructure systems [51; 52; 53]. Notably, considerable attention has been paid to two pivotal systems: Electric Power Supply Systems (EPSSs) and transportation systems (TSs). These two CISs play a strategically crucial role in ensuring the continuity of functionality and the robust recovery of all the other interconnected systems. Specifically, regarding EPSSs, [PERSON] et al. [54] established a link between the seismic robustness of EPSSs and the fragility behaviour of their most critical components under damaging earthquakes. Their proposed modelling framework allows the quantification of the system-level cost of seismic damage, along with corresponding socio-economic losses. [PERSON] and [PERSON] [55] proposed a framework for modelling the impact of cascading failures across EPSSs. Within this framework, the overload resulting from cascades is characterized by a tolerance parameter, which assesses the element flow capacity relative to flow demands in real-world EPSSs. The study indicates that enhancing component tolerance alone does not guarantee EPSS robustness in the face of disproportionate cascading failures. Simultaneously, topological upgrades play a crucial role in enhancing the cascade robustness of the system, particularly when operating at viable tolerance levels. Within the framework of game theory, [PERSON] and [PERSON] [56] employed mechanism design to introduce an economic model specifically targeting the post-shock recovery of EPSSs. Their research underscores that the prolonged restoration time of EPSSs, as well as other CISs, may stem from insufficient coordination among system operators. As a result,the adoption of incentive-compatible contracts emerges as a strategic approach for shaping effective emergency restoration plans, thereby significantly enhancing social welfare. [PERSON] et al. (2020) established an agent-based model (ABM), a bottom-up and adaptive computational approach to large-scale socio-economic systems ([PERSON] et al., 2020), to address the post-shock recovery of earthquake-damaged EPSSs. This study highlights the emergence of potentially conflicting interests between the community and the EPSS operator. Resolving such conflicts would reshape the recovery dynamics of the integrated EPSS-community. Additionally, this study demonstrates the importance of the development of seismic contingency dispatch strategies and contingency demand regulation measures to enhance the societal resilience of EPSS-communities. Vis-a-vis TSs, [PERSON] et al. (2020) introduced a comprehensive framework aimed at quantifying both the repair cost and repair time of bridge structures. These structures play a pivotal role in modern TSs, particularly highway networks. In such a framework, these two measures are obtained by linking the amounts of repair materials, to damage states requiring the repair, to structural response causing the damage, and eventually to the intensity measure of seismic hazards. By disaggregating these components, the framework provides detailed insights into the damage and failure of individual bridge members. Consequently, it facilitates informed decision-making regarding both structural design and retrofit strategies. [PERSON] et al. (2020) proposed a probabilistic model to evaluate the seismic resilience of bridges. This model utilizes fragility functions to assess the earthquake-induced physical damage of a specific bridge. Subsequently, considering varying levels of initial damage and different rates of rehabilitation, a probabilistic six-parameter sinusoidal-based function is established. This function shapes the recovery trajectory of bridge structures, enabling risk-informed decision-makings. Regarding the post-shock recovery of TSs, [PERSON] et al.