Artificial Cognitive Systems

Prof. David Vernon
Carnegie Mellon University Africa
Rwanda
vernoncmu.edu


Course Outline  |  Lecture Notes  |  Course Textbook  |  Recommended Reading  |  Useful Links

Course Outline

The Nature of Cognition

  • Overview
  • Motivation for studying artificial cognitive systems
  • Aspects of modelling cognitive systems
  • So, what is cognition anyway?
  • Levels of abstraction in modelling cognitive systems

Paradigms of Cognitive Science

  • The cognitivist paradigm of cognitive science
  • The emergent paradigm of cognitive science
  • Hybrid Systems
  • A comparison on cognitivist and emergent paradigms
  • Which paradigm should we choose?
Cognitive Architectures
  • What is a cognitive architecture?
  • Desirable characteristics
  • Designing a cognitive architecture
  • Example cognitive architectures
  • Cognitive architectures: what next?
Autonomy
  • Types of Autonomy
  • Robotic Autonomy
  • Biological Autonomy
  • Autonomic Systems
  • Different Scales of Autonomy
  • Goals
  • Measuring Autonomy
  • Autonomy and Cognition
  • A Menagerie of Autonomies
Embodiment
  • Cognitivist perspective on embodiment
  • Emergent perspective on embodiment
  • The impact of embodiment on cognition
  • Three hypotheses on embodiment
  • Evidence for the embodied stance: the mutual dependence of perception and action
  • Types of embodiment
  • Off-line embodied cognition
  • Interaction within
  • From situation cognition to distributed cognition
Development and Learning
  • Development
  • Phylogeny vs. Ontogeny
  • Development from the perspective of psychology
Memory and Prospection
  • Types of memory
  • The role of memory
  • Self-projection, prospection, and internal simulation
  • Internal simulation and action
  • Forgetting
Knowledge and Representation
  • The duality of memory and knowledge
  • Representation and anti-representation
  • The symbol grounding problem
  • Joint perceptuo-motor representations
  • Acquiring and sharing knowledge
Social Cognition
  • Social interaction
  • Reading intentions and theory of mind
  • Instrumental helping
  • Collaboration
  • Development and interaction dynamics

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Lecture Notes

Slide Format
Lecture 1: The Nature of Cognition  
Lecture 2: Paradigms of Cognitive Science  
Lecture 3: Cognitive Architectures  
Lecture 4: Autonomy  
Lecture 5: Embodiment  
Lecture 6: Development and Learning 
Lecture 7: Memory and Prospection  
Lecture 8: Knowledge & Representation  
Lecture 9: Social Cognition  

Handout Format
Lecture 1: The Nature of Cognition  
Lecture 2: Paradigms of Cognitive Science  
Lecture 3: Cognitive Architectures  
Lecture 4: Autonomy  
Lecture 5: Embodiment  
Lecture 6: Development and Learning 
Lecture 7: Memory and Prospection  
Lecture 8: Knowledge & Representation  
Lecture 9: Social Cognition  

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Course Textbook

D. Vernon, Artificial Cognitive Systems, MIT Press (2014).

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Recommended Reading

Duch, W, Oentaryo, R. J., and Pasquier, M. Cognitive Architectures: Where do we go from here?, Proc. Conf. Artificial General Intelligence, 122-136 (2008).

Langley, P.: Cognitive architectures and general intelligent systems. AI Magazine 27(2), 33-44 (2006).

Langley, P., Laird, J.E., Rogers, S.: Cognitive architectures: Research issues and challenges. Cognitive Systems Research 10(2), 141-160 (2009).

Merrick, K. E. A Comparative Study of Value Systems for Self-motivated Exploration and Learning by Robots, IEEE Transactions on Autonomous Mental Development, Vol. 2, No. 2, 119-131 (2010).

Sun, R.: The importance of cognitive architectures: an analysis based on clarion. Journal of Experimental & Theoretical Artificial Intelligence 19(2), 159-193 (2007).

Sun, R.: Desiderata for cognitive architectures. Philosophical Psychology 17(3), 341-373 (2004).

Vernon, D. Cognitive System, Computer Vision: A Reference Guide, Springer (2014).

Vernon, D. Cognitive Vision: The Case for Embodied Perception, Image and Vision Computing, Special Issue on Cognitive Vision, Vol. 26, No. 1, pp. 127-141 (2008).

Vernon, D., Metta. G., and Sandini, G. A Survey of Artificial Cognitive Systems: Implications for the Autonomous Development of Mental Capabilities in Computational Agents, IEEE Transactions on Evolutionary Computation, special issue on Autonomous Mental Development, Vol. 11, No. 2, pp. 151-180 (2007).

Vernon, D., von Hofsten, C., and Fadiga, L. A Roadmap for Cognitive Development in Humanoid Robots, Cognitive Systems Monographs (COSMOS), Springer, ISBN 978-3-642-16903-8 (2010).

Vernon, D. Reconciling Autonomy with Utility: A Roadmap and Architecture for Cognitive Development", Proc. Int. Conf. on Biologically-Inspired Cognitive Architectures 2011, A. V. Samsonovich and K. R. Johannsdottir (Eds.), IOS Press, 412-418 (2011).

Vernon, D. and Furlong, D. Philosophical Foundations of Enactive AI, in 50 Years of AI, M. Lungarella et al. (Eds.), Festschrift, LNAI 4850, Springer-Verlag, Heidelberg, pp. 53-62 (2007).

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Useful Links

Please refer to my wiki for links to related resources and support material, including tutorials, research networks, and degree programmes in artificial cognitive systems.

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David Vernon's Personal Website