Cognitive computation: A case study in cognitive control of autonomous systems and some future directions

Cognitive computation is an emerging discipline linking together neurobiology, cognitive psychology and artificial intelligence. Springer Neuroscience has launched a journal in this exciting multidisciplinary topic, which seeks to publish biologically inspired theoretical, computational, experimental and integrative accounts of all aspects of natural and artificial cognitive systems. In this keynote, we outline and build on some of the pioneering work of the late Professor John Taylor, who was also founding Advisory Board Chair of Cognitive Computation, specifically his proposal on how to create a cognitive machine equipped with multi-modal cognitive capabilities. In this context, we first present a novel modular cognitive control framework for autonomous systems that could potentially realize the required cognitive action-selection and learning capabilities in Professor Taylor´s envisaged cognitive machine. An ongoing case study in autonomous vehicle control is described, as a benchmark problem, with encouraging preliminary results in a range of realistic driving scenarios - and with significant potential fuel and emission economy implications, compared to conventional control systems. Finally, possible future avenues are explored, including our ongoing work aimed at developing a general modular cognitive framework incorporating multiple modalities, including vision, motor action, language and emotion, required for enabling multi-modal social cognitive and affective behavioral capabilities in future autonomous agents.