This course develops a multidisciplinary approach to the theory, methods, and current issues across the member disciplines of the Cognitive Systems program. The perspectives of these disciplines are integrated by way of general principles of information representation and processing. Central to this are the ways that information can be represented and processed by any cognitive system, both natural and artificial.
The goal of this course is to help you think creatively and critically about integrating various approaches to the understanding and design of cognitive systems. The lectures will focus on issues such as theories of mind and intelligence, computational characterizations of agents in complex environments, situated cognition, communication, and interaction, both from the perspective of artificial and natural systems. In tandem the laboratories will provide a “hands on” way of investigating some of these topics experimentally.
Topics discussed include: Symbolic representation, Connectionism and new AI, iqr large-scale neuronal simulator, Vision in natural systems, Vision in artifacts, Attention, Multi-sensory integration, Methods for Systems Design, Emotion in humans, Emotion in artifacts: Affective computing, Learning in natural systems, Artificial learning and memory, Architectures and modularity, Massive modularity, Consciousness and self models, Game theory, Neuroeconomics, Social-Cognition Model, Social neuroscience
The formal prerequisite is COGS 200. PSYC 100, CPSC 110 and CPSC 121 are recommended.