Cog Sci 2014 - Workshop on AGI and Cognitive Science

Artificial General Intelligence is not simply AI reloaded, but may be best understood as a sub-discipline of Cognitive Science. AGI treats cognition and the mind as computational phenomena, and either strives to replicate (and exceed) human cognitive performance, or treat human and animal minds as specific cases of a more general class of intelligent system to be explored.
In the early years of the AI field, the leading approaches were mostly characterized by an understanding of cognition as the manipulation of rather abstract representations: the integration of real-world perception and action, autonomous learning, motivation and emotion were usually outside the scope of the models. AI has since seen several broad movements, including connectionism, statistical/probabilistic learning and modeling, and robotic systems.
Today, most work in AI focuses on applications or abstract methods rather than building mind-like systems. In contrast, AGI remains aimed at an understanding of the mind, in the context the progress in computational neuroscience and new insights into affect, motivation, autonomy, perceptual processing, attention, sociality, language, and so on.AGI is not well aligned with the boundaries of existing disciplines, but must draw from many fields. Unlike most work in the other sub-disciplines of Cognitive Science, AGI is ultimately always concerned with the creation of complete working systems and the identification of general functional principles, which are abstracted as algorithms and architectures.
AGI has to be informed by our best understanding of the mind, and thus cannot afford ignorance of cognitive neuroscience, cognitive and developmental psychology, linguistics, and philosophy of mind, to name just a few of the relevant fields. On the other hand, the constructionist approach of AGI offers a methodology to formulate, integrate and test theories from various cognitive sciences as computational simulations. AGI also offers formalisms, terminology and working systems that can potentially be applied to many individual problems of the other sub-disciplines of Cognitive Science.
Example Topics
In this workshop we want to explore and discuss AGI’s integration and role within Cognitive Science. We especially invite contributions with regard to
Making results from other cognitive sciences fruitful to AGI
Applications of AGI in other disciplines
Cognitive modeling
Intelligent agents
Integrated architectures
Experimental methodology
Challenges to AGI’s existing approaches
Methodological and epistemological issues
History of AI and Cognitive Science
Possible areas of collaboration between AGI and other aspects of Cognitive Science
Workshop Chair: Joscha Bach
Workshop Organizing Committee: Joscha Bach, Glenn Gunzelmann