This paper presents an agent architecture interaction assessment framework developed using constructsand measures from architecture 11,12, 18, 26, 27, 28, 35, 46, agent-based modeling 15, 52, humanfactors 36, 38, 39, 40, 45, 49, 50, 51, systems science engineering 5, 6, 17, 12, cognitive science 1,13, 20, 22, 23, 41, 47, 48, 53, neuroscience 19, 20, 37 and evolutionary biology 19, 34, 42. This workelaborates the ANFA Conference Mission, “…the range of human experiences that occur in context withelements of architecture, both exterior and interior...” by expanding the constructs of ‘human’ to ‘agent’and ‘elements of architecture’ to include all physical and non-physical architectures that function as partof an agent’s ecological niche 18. This reframing of the constructs of and relationships between humansand architecture is useful for modeling and analyzing interactions between humans, other intelligentagents, and their environments, because it puts all agents and environmental elements into one unifiedrepresentational framework, defining them through a single, consistent, comprehensive schema withshared constructs and measures. This agent-based information processing systems assessmentframework is especially useful now, as designers and researchers develop new constructs, methods, andtools for modeling, analyzing, simulating, and designing smart environments (e.g., smart cities, intelligentbuildings, interactive environments, augmented cognition, etc.) 3, 4, 26,43. As part of expanding thesense of what constitutes a ‘cognizing agent’ and an ‘architecture’, readers/attendees are introduced toemerging system types, including: complex, interactive architectural systems (CIAS) 1, cyber-physicalsystems (CPS) 16, 24, 25, 31, 32, 54, 55, socio-technical systems (STS) 14, cyber-social systems(CSS) 30, ultra-large scale systems (ULS) 33, complex, large, integrated, open systems (CLIOS) 10,29, 44, multi-scale systems (MSS) 21, and the Internet-of Things-Enabled Smart City Framework 4,30. These emerging systems entail increased complexity, a high degree of real-time interactivitybetween agents (people, buildings, other organisms, hardware, software), and an accelerated rate ofadaptation/evolution 26.
Joe Manganelli (Sun,) studied this question.