PhASiC

PhASiC, or Physical Augmented Systems Intelligence and Computing, brings together virtual environments, regulatory psychophysiology, and intelligence augmentation (IA). As an inverse approach to AI, PhASiC utilizes extended reality (an expansive definition of XR) to enable intelligence augmentation. Allostasis machines (dynamical representations of psychophysiological interactions with the environment) both interact with XR (as a simulated form of the environment) and regulate IA.

PhASiC is a project housed within the Representational Brains & Phenotypes working group at Orthogonal Research and Education Lab.

Physical Intelligence / Intelligence Augmentation (IA) Publications

• An Integrative Introduction to Human Augmentation Science. arXiv, 1804.10521 (2018). paper
• Naturally Supervised Learning in Motion and Touch-driven Technologies. arXiv, 1106:1105 (2011). paper
• Stochastic Resonance (SR) can drive adaptive physiological processes. Nature Precedings, npre.2009.3301.1 (2009). paper
• Range-based techniques for discovering optimality and analyzing scaling relationships in neuromechanical systems. Nature Precedings, npre.2009.2845.2 (2009). paper
• The adaptability of physiological systems optimizes performance: new directions in augmentation. arXiv, 0810.4884 (2008). paper
• Performance Augmentation in Hybrid Systems: techniques and experiment. arXiv, 0810.4629 (2008). paper