Computational Collective Intelligence. Technologies and by Jan Treur (auth.), Piotr Jędrzejowicz, Ngoc Thanh Nguyen,
By Jan Treur (auth.), Piotr Jędrzejowicz, Ngoc Thanh Nguyen, Kiem Hoang (eds.)
The two-volume set LNAI 6922 and LNAI 6923 constitutes the refereed court cases of the 3rd overseas convention on Computational Collective Intelligence, ICCCI 2011, held in Gdynia, Poland, in September 2011.
The 112 papers during this quantity set provided including three keynote speeches have been conscientiously reviewed and chosen from three hundred submissions. The papers are geared up in topical sections on wisdom administration, desktop studying and functions, self reliant and collective decision-making, collective computations and optimization, internet providers and semantic net, social networks and computational swarm intelligence and applications.
Read or Download Computational Collective Intelligence. Technologies and Applications: Third International Conference, ICCCI 2011, Gdynia, Poland, September 21-23, 2011, Proceedings, Part I PDF
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Extra resources for Computational Collective Intelligence. Technologies and Applications: Third International Conference, ICCCI 2011, Gdynia, Poland, September 21-23, 2011, Proceedings, Part I
306–316. Springer, Heidelberg (2011) 40. : Einfühlung, innere Nachahmung und Organempfindung. Archiv für die Gesamte Psychologie 1, 465–519 (1903) 16 J. Treur 41. : An Agent Model for Cognitive and Affective Empathic Understanding of Other Agents. M. ): ICCCI 2009. LNCS, vol. 5796, pp. 279–293. Springer, Heidelberg (2009) 42. : Re-valuing the amygdala. Current Opinion in Neurobiology 20, 221–230 (2010) 43. : Single-Neuron Responses in Humans during Execution and Observation of Actions. Current Biology 20, 750–756 (2010) 44.
91-92; , pp. 119-122): emotion felt = based on sensory representation of (simulated) bodily changes → preparation for bodily changes = emotional response This provides a cyclic process that (for a constant environment) can lead to equilibrium states for both, as shown, for example, in  by a computational model. , , ). Here (1) breaks with the tradition that there is a standard order of processing sensing – internal processing – preparation for action, and (2) allows for involving body representations in internal processes without actually having to change any body state.
E. that “has knowledge, develops it, and applies it” . Trying to answer this need which is yet to be fulfilled, we propose in our research a smart administration system able to store, develop, improve and apply knowledge. Experiential Knowledge in the Development of Decisional DNA 19 • Second, European and Australian studies reported in  have established that the primary research aim of KM should be to use the vast experience that is accumulating each day within organisations, as true knowledge is build up through learning from current and past experiences [3,11,12].