  Symbiotic Autonomous Systems (SAS) are advanced intelligent and cognitive
systems exhibiting autonomous collective intelligence enabled by coherent
symbiosis of human-machine interactions in hybrid societies. Basic research in
the emerging field of SAS has triggered advanced general AI technologies
functioning without human intervention or hybrid symbiotic systems synergizing
humans and intelligent machines into coherent cognitive systems. This work
presents a theoretical framework of SAS underpinned by the latest advances in
intelligence, cognition, computer, and system sciences. SAS are characterized
by the composition of autonomous and symbiotic systems that adopt
bio-brain-social-inspired and heterogeneously synergized structures and
autonomous behaviors. This paper explores their cognitive and mathematical
foundations. The challenge to seamless human-machine interactions in a hybrid
environment is addressed. SAS-based collective intelligence is explored in
order to augment human capability by autonomous machine intelligence towards
the next generation of general AI, autonomous computers, and trustworthy
mission-critical intelligent systems. Emerging paradigms and engineering
applications of SAS are elaborated via an autonomous knowledge learning system
that symbiotically works between humans and cognitive robots.
