# Spatiotemporal Modeling of the Smart City Residents' Activity with Multi-Agent Systems
## 2 Related Works
[PERSON], in [29], prototyped CityMatrix, which is an evidence-based urban decision support system, augmented by artificial intelligence (AI) techniques, including machine learning simulation predictions and optimization of search algorithms. [PERSON] investigated the strength of these technologies to augment the ability to make better urban decisions. [PERSON], [PERSON], and [PERSON], in [30], investigated a smartphone-based augmented reality architecture as a tool for aiding public participation in urban planning by developing a prototype system, which showed 3D virtual representations of proposed architectural designs visualized on top of the existing real-world architecture. The authors investigated whether using a smartphone augmented reality system increases the willingness of the public to participate and the perceived participation in urban planning. [PERSON] and [PERSON] [31] built a support vector machine (SVM) model to predict the trends of coordinated development. The authors compared the method with an artificial neural network, decision tree, logistic regression, and naive Bayesian classifier regarding the urban ecosystem coordinated development prediction for the Guanzhong urban agglomeration. [PERSON], [PERSON], and [PERSON], in [32], used techniques of machine learning and data mining to discover comprehensible and useful structures in the multivariate municipality data. As [PERSON] and [PERSON] in [33] indicate, \"Urban Data Mining represents a methodological approach that discovers logical, mathematical and partly complex descriptions of urban patterns and regularities inside statistical data\". In the conducted research, multi-agent systems were adopted as a tool for modeling and simulation. It enabled the implementation of the assumptions behind the actor-network theory for modeling social processes in the urban space of a smart city. A multi-agent system (MAS or a \"self-organized system\") is a computerized system composed of multiple interacting intelligent agents (see [9; 34]). Multi-agent systems can solve problems that are difficult or impossible for an individual agent or a monolithic system to solve. The primary assumption of MAS is communication amongst the agents and their autonomy. The notion of agents, as currently used in urban simulation models, is a kind of automaton that mimics the behavior of urban agents in a predetermined way. [PERSON], in [35], describes a CogCity (cognitive city) as an urban simulation model that explicitly incorporates in its structure the role of three cognitive processes that typify the behavior of human agents: Information compression, cognitive mapping, and categorization. Moreover, the model CogCity demonstrates the possibility and usefulness of agent-based and cellular automata urban simulation model, which combines top-down and bottom-up processes in one model. Projects from MIT's SENSEable City Lab foster the vision of the real-time city by providing 'a feedback loop between people, their actions, and the city'. The issue of public opinion formation is the subject of studies conducted by [PERSON], [PERSON], and [PERSON] in [36], and [PERSON] and [PERSON] in [37]. These authors consider the issue of social opinion formation through consensus, polarization, and fragmentation. The article investigates various models for the dynamics of continuous opinions by analytical methods as well as by computer simulations. Consequently, the rapid development of advanced technologies (IoT, wearable computing, etc.) forces the process of connecting real-world objects like buildings, roads, household appliances, and human bodies to the Internet via sensors and microprocessor chips that record and transmit data such as sound waves, temperature, movement, and other variables. This supports the development of smart citizens (see [38]). In [39], [PERSON] points to correlation between the urban form and the urban performance, e.g., the quality of life, vibrancy, and safety.