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We present a sequential distributed model predictive control (MPC) scheme for cooperative control of multi-agent systems with dynamically decoupled heterogeneous nonlinear agents subject to individual constraints. In the scheme, we explore…
In this paper, we investigate the distributed optimal control problem for a kind of nonlinear multi-agent systems. In particular,both the state and the system dynamic structures of each agent are private and can only be shared among…
Cloud computing systems promise to offer subscription-oriented, enterprise-quality computing services to users worldwide. With the increased demand for delivering services to a large number of users, they need to offer differentiated…
The concept of Energy Hub (EH) has been emerged to accommodate renewable energy sources in a multi-energy system to deploy the synergies between electricity and other energy sources. However, the market mechanisms for the integration of the…
The increasing demand for energy-efficient solutions in large-scale infrastructure, particularly data centers, requires advanced control strategies to optimize environmental management systems. We propose a multi-agent architecture for…
This paper studies the joint optimization of edge node activation and resource pricing in edge computing, where an edge computing platform provides heterogeneous resources to accommodate multiple services with diverse preferences. We cast…
Algorithm selection and hyperparameter tuning are critical steps in both academic and applied machine learning. On the other hand, these steps are becoming ever increasingly delicate due to the extensive rise in the number, diversity, and…
In this paper, we propose a distributed control strategy for the design of an energy market. The method relies on a hierarchical structure of aggregators for the coordination of prosumers (agents which can produce and consume energy). The…
Handling the massive number of devices needed in numerous applications such as smart cities is a major challenge given the scarcity of spectrum resources. Dynamic spectrum access (DSA) is seen as a potential candidate to support the…
Infrastructure-as-a-Service providers are offering their unused resources in the form of variable-priced virtual machines (VMs), known as "spot instances", at prices significantly lower than their standard fixed-priced resources. To lease…
Resource distribution is a fundamental problem in economic and policy design, particularly when demand and supply are not naturally aligned. Without regulation, wealthier individuals may monopolize this resource, leaving the needs of others…
Industrial symbiosis fosters circularity by enabling firms to repurpose residual resources, yet its emergence is constrained by socio-spatial frictions that shape costs, matching opportunities, and market efficiency. Existing models often…
Machine learning (ML) algorithms are showing a growing trend in helping the scientific communities across different disciplines and institutions to address large and diverse data problems. However, many available ML tools are…
This paper explores multi-agent systems and identify challenges that remain inadequately addressed. By leveraging the diverse capabilities and roles of individual agents, multi-agent systems can tackle complex tasks through agent…
Transactive energy systems (TES) are emerging as a transformative solution for the problems that distribution system operators face due to an increase in the use of distributed energy resources and rapid growth in scalability of managing…
Large multi-tenant production clusters often have to handle a variety of jobs and applications with a variety of complex resource usage characteristics. It is non-trivial and non-optimal to manually create placement rules for scheduling…
Business process simulation is a versatile technique to predict the impact of one or more changes on the performance of a process. Mainstream approaches in this space suffer from various limitations, some stemming from the fact that they…
In several smart city applications, multiple resources must be allocated among competing agents that are coupled through such shared resources and are constrained --- either through limitations of communication infrastructure or privacy…
In this chapter we will argue that studying such multi-scale multi-science systems gives rise to inherently hybrid models containing many different algorithms best serviced by different types of computing environments (ranging from…
Nowadays, data-centers are largely under-utilized because resource allocation is based on reservation mechanisms which ignore actual resource utilization. Indeed, it is common to reserve resources for peak demand, which may occur only for a…