The ability for strategy change, i.e., the change in action selection and action planning while an overarching goal is maintained is a fundamental, but still barely understood capability of cognitive systems. Sudden transitions are well documented in neurophysiological and cognitive experimental data, but application of the underlying theory of the spatio-temporal neurodynamics is yet to be done. Current physiological and theoretical frameworks of learning focus on incremental learning (as exemplified the reinforcement learning). This project aims at improved understanding of the nature and functional role of abrupt, large-scale state transitions in complex neuronal systems as the basis of cognitive strategy change. We exploit our experimental and theoretical understanding of a particular rodent learning model to simulate the neuronal mechanisms of instantaneous strategy change. The investigators will develop an algorithmic formulation of the neurocomputational principles, and apply it in the engineering example of autonomous vehicle control. This interdisciplinary project is based on the complementary and synergistic expertise of the team members in optimization theory and both theoretical and experimental neuroscience.
This project arises from our deep understanding of the rapid biological and cognitive processes displayed by strategy changes in coping with changing environments. This research on decision making in human and animal brains provides a platform for developing robust decision support systems that operate in dynamically changing scenarios in the style of brains. Detailed analysis of the mechanisms underlying rapid strategy change in brains will allow both this research team and other groups to equip various man-made systems with the fundamental property of insightful cognition. This work addresses important societal needs by creating the foundations of cognitive engineering systems supporting emergency response to natural disasters and cyber security threats by adversaries, as well as optimized control of autonomous vehicles under complex operating conditions.
This award is being co-funded by NSF's Office of International Science and Engineering. A companion project is being funded by the German Ministry of Education and Research (BMBF).
