Brain Inspired Cognitive Systems 2008 by Gaëlle Spielmann Moura, Yolanda Triñanes-Pego, Maria T.

By Gaëlle Spielmann Moura, Yolanda Triñanes-Pego, Maria T. Carrillo-de-la-Peña (auth.), Amir Hussain, Igor Aleksander, Leslie S. Smith, Allan Kardec Barros, Ron Chrisley, Vassilis Cutsuridis (eds.)

Brain encouraged Cognitive structures 2008 (June 24-27, 2008; São Luís, Brazil) introduced jointly prime scientists and engineers who use analytic, syntactic and computational equipment either to appreciate the prodigious processing houses of organic platforms and, particularly, of the mind, and to take advantage of such wisdom to strengthen computational tools in the direction of ever larger degrees of cognitive competence.

This booklet comprises the papers provided at 4 significant symposia:

Part I - Cognitive Neuroscience

Part II - Biologically encouraged Systems

Part III - Neural Computation

Part IV - types of Consciousness.

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Nature - Neuroscience, VOL 5 - February 2004 pp. 97–107. (2004) 34. White, J. , Thompson, J. : . The structure of the nervous system of the nematode C. Elegans. Phil. Trans. R. Soc. London 314, pp. 1–340. (1986) Agent-Based Cognitive Model for Human Resources Competence Management Stefan Oliveira and Jo˜ao Carlos Gluz Abstract This chapter presents an agent-based cognitive model aimed to represent human competency concepts and competence management processes of psychological nature. This model is implemented by a multiagent system application intended to help managers of software development projects to select, based on the competence management model, the right professionals to integrate a development team.

The two other functors had to be implemented by hand, using the following algorithm: 1. For each new pattern unmapped by any CR, create new level 1 CR 2. CR Cycle, comprising of 4 substeps: a. Build the landscape, by assigning a Record node in the memory to the active pattern, if more than one Record is active, create a level C1 Record, if already at levelC1, create a new levelC1 CR to handle that new Record; b. Choose a Procedure, by following the activator links from the current Record to next Procedures, if none, add one to recreate the current pattern, if more than one create a level C1 Procedure, if already at levelC1, create a new levelC1 CR to handle that new Procedure; c.

This Memory is subdivided in three: Empirical - where nodes represent Records of previous experiences; Procedural - with nodes representing Procedures bound to known actions options or strategies; Semantic - a higher level memory containing nodes named Concepts, representing classes of equivalences between records or procedures; The MES is connected to receptors and actuators that translates information from the environment in form of nodes and links. The patterns of active nodes and links in the receptors are bound to Record colimits in the empirical part of the Memory and active patterns in the actuators are bound to Procedures limits in the procedural memory.

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