Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Architectural Engineering

In the last 250 years, the world has become more perceivable, and aware of the perpetual growth of complex information and meanings in urban, social, and environmental systems. This should have invited a responsive interdisciplinary philosophy to planning and complexity sciences, for modelling complex systems in the generated realm of unknown and inexplicable complexities. Here, we discuss challenges facing such aim. Next, we develop a novel relevant integrative philosophy of a general model that extends world line understandings of self-organization in socio-physical systems, to face these perpetual complexities that are related to chaos phenomena. Relevantly, to utilize this novel understanding and self-organization model, we find that the chronic growth of these networked complexities in today{u2019}s world, now require highly efficient evolvable systems. However, diverse issues are facing urban planning due to the limitations of artificial intelligence (AI) planning tools. These incapacities have relatively limited our ability to perceive and handle possible temperamental situations in socio-physical contexts and in real-time modes. We theoretically present two philosophical and systematic causal models to address this dilemma. The first model evaluates current directions in AI and AI planning tools. The second causal model proposes further alignment to urban self-organizational happenings, by putting philosophical foundations for a responsive artificial superintelligence ASI

Issued also as CD