Cognition Dynamics: Time and Change Aspects in Quantitative Cognitics
Cognition, and automated cognition i.e. cognitics, have recently been given a theoretical framework, whereby core concepts have been formally defined, along with metric units. Beyond intellectual exploration and cultural interest, this was also motivated by the goal to automate cognition, i. e. to carry over some of the cognitive processes and tasks from humans to machine-based artifacts. First achievements have led to a number of interesting new results. One of them is to make explicit and more evident than in the past the critical role, in cognitics, of time and change quantities, as well as of the coercive level of control actions, along with perturbations and system properties. After a brief reminder of essential definitions, the paper reports on these topics, describing and discussing a number of complementary aspects summarized in title: 1. time and abstraction levels, which lead to various time properties and possibly specific orders of stationarity; 2. time based difference between knowledge and expertise; 3. critical role of time in estimation of information quantities, and thereby in particular in the estimation of complexity and knowledge quantities; 4. explanation, straightforward in this context, of the apparent so-called “paradoxes of experts”, in learning and forecasting; 5. importance of time in automation as well, more specifically in loop control, where some time properties of control path (including perception, decision and action phases) relatively to those of system behavior (here the system is the entity to be controlled) are critical for success; 6. time and changes interrelations, with necessity, for quantitative estimation, of considering other factors as well; 7. possible changes of system time properties, in the context of closed loop control, whereby large differences may occur with respect to those in natural (open loop) status, depending on action and perturbation intensities, as well as on possible overall non-stationarities and non-linearities; 8. driving causes for changes, and classical analogies in the context of human psyche and cognition dynamics. The paper illustrates discussions with concrete examples relating to Robocup-at-Home competition tests and applications.
KeywordsCognitive Domain Cognitive System Time Property Human Psyche Cognition Dynamics
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- 1.Robocup Federation (9.2.2009), http://www.robocup.org/
- 3.Dessimoz, J.-D., Gauthey, P.-F., Kjeldsen, C.: Ontology for Cognitics, Closed-Loop Agility Constraint, and Case Study in Embedded Autonomous Systems – a Mobile Robot with Industrial-Grade Components. In: Proc. Conf. INDIN 2006 on Industrial Informatics, August 14-17, p. 6. IEEE, Los Alamitos (2006)Google Scholar
- 4.Dessimoz, J.-D.: La Cognitique - Définitions et métrique pour les sciences cognitives et la cognition automatisée, Editions Roboptics, Yverdon-les-Bains, Switzerland (August 2008) ISBN 978-2-9700629-0-5Google Scholar
- 5.Dessimoz, J.-D.: Contributions to Standards and Common Platforms in Robotics; Prerequisites for Quantitative Cognitics. In: International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR) 2008. First International Workshop on Standards and Common Platform for Robotics, Venice, Italy, October 3-7 (2008)Google Scholar
- 6.Dietrich, E., Markman, A.B. (eds.): Cognitive Dynamics: Conceptual and Representational Change in Humans and Machines. Lawrence Erlbaum Associates, Mahwah (2000)Google Scholar
- 7.De Gyurky, S.: The Cognitive Dynamics of Computer Science, Cost-Effective Large Scale Software Development. Wiley, Chichester (2006)Google Scholar
- 8.Wikipedia Foundation (5.2. 2009), http://en.wikipedia.org/wiki/Main_Page
- 9.HEIG-VD website (6.5.2009), http://rahe.populus.ch/rub/4.
- 10.Nardi, D., et al.: Rulebook, Draft edition (February 2009), http://www.ai.rug.nl/robocupathome/documents/rulebook2009_DRAFT.pdf