Abstracts Economics

Decentralized Intelligent Decision Making in Cyber Physical Social Systems

by Nathan Patrizi

The accelerated evolution towards jointly considering the physical, cyber, and social space is expected to dramatically increase the interest of the research and industrial community to build efficient, resilient, and secure Cyber Physical Social Systems. In this dissertation, we focus our research activities on devising decentralized intelligent decision making models, frameworks, and algorithms to support the smooth operation of Cyber Physical Social Systems. The proposed decentralized intelligent decision making models are jointly exploiting theories from the field of Economics, such as Game Theory and Contract Theory, and from the field of Computer Science, such as Reinforcement Learning concepts. Reinforcement learning is applied to allow for humans to make informed decisions in the considered Cyber Physical Social Systems based off of the dynamically changing environment around them. Additionally, contract theoretic and game theoretic models allow for us to accurately depict the relationships between the different involved entities in the examined system. Several research problems have been examined which can be summarized as follows: (i) socio-physical human orchestration in smart cities, (ii) socio-aware public safety framework design, (iii) unmanned aerial vehicle or UAV-enabled dynamic multi-target tracking and sensing framework, (iv) resource orchestration in wireless powered communication public safety systems, (v) health data acquisition from wearable devices during a pandemic by following a techno-economics approach, (vi) museum and visitor interaction and feedback orchestration enabled by labor economics, and (vii) design and operation of prosumer-centric self-sustained smart grid systems. Finally, all the above problems are thoroughly evaluated and tested via a series of simulations and emulations with regards to the main characteristics of their operation, as well as against other approaches from the literature.