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manuscript. Sun, R. 2006. The CLARION cognitive architecture: Extending cognitive modeling to social simulation. In R. Sun (Ed.), Cognition and multi-agent interaction, 79-99. New York: Cambridge University Press.

://en.oxforddictionaries.com/word-of-the-year/word-of-the-year-2016 Oxford English dictionary . Available at: http://www.oed.com/ Ruiz de Mendoza, F.J. & Galera Masegosa, A. (2014). Cognitive modeling. A linguistic perspective . Amsterdam-Philadelphia: John Benjamins. Ruiz de Mendoza, F.J. & Galera Masegosa, A. (2011). The contemporary theory of metaphor: Myths, developments and challenges. In Metaphor and symbol , 26, p.1-25. Sia partners (2016). BREXIT OR BREMAIN: A major difference for the powerhorse called European Union? Available at: http://en.finance.sia-partners.com/20160623/brexit

. 2007. Learning to control a dynamic task: A system dynamics cognitive model of the slope effect. In Proceedings of the 8th International Conference on Cognitive Modeling , 61-66. Ann Arbor, MI. Halbrügge, M. in press. Keep it simple - A case study of model development in the context of the Dynamic Stock and Flows (DSF) task. Journal of Artificial General Intelligence . Kase, S.E., Ritter, F.E., and Schoelles, M. 2007. Using HPC and PGAs to optimize noisy computational models of cognition. In Innovations and Advanced Techniques in Systems, Computing Sciences and

, Consciousness, Culture, Cambridge: MIT Press. Konderak P. (2005). Model kognitywny zdolności językowych. PhD Thesis. Konderak P. (2007). Modularność umysłu, modularność języka. In Sz. Wrobel (ed.) Modularność umysłu. Poznań-Kalisz: WP-A UAM, 179-206. Konderak P. (2015). On a Cognitive Model of Semiosis, Studies in Logic, Grammar and Rhetoric 40 (53), 129-144. Levelt W. J.M. (2000). Producing Spoken Language: a Blueprint of the Speaker. In C.M., P. Hagoort (eds), The Neurocognition of Language, Oxford University Press: New York, 83-122. Merleau-Ponty M. (1962). Phenomenology

.; and Hubbard, S. M. 2002. Oscillation in Beliefs and Decisions. In The persuasion handbook: developments in theory and practice. Thousand Oaks, CA: Sage. Gluck, K.; Halbruegge, M.; Moore, R.; Reitter, D.; and Stanley, C. 2010. Parameter space exploration in cognitive models. Journal of Artificial General Intelligence 2(2). Gonzalez, C., and Lebiere, C. 2005. Instance-based cognitive models of decision making. In Zizzo, D., and Courakis, A., eds., Transfer of knowledge in economic decision making. New York: Palgrave McMillan. Gonzalez, C.; Lerch, F.; and Lebiere

Abstract

The paper addresses the concept of ‘death’ and the way it can be presented in the form of a semantic frame. Owing to a considerable diversity of approaches between various cultures and religions, the cognitive model illustrated in the present discussion depicts the European perspective. The analysis helps to establish the elements of the frame together with their lexical exponents employed in language, which are conditioned on the worldview adopted by a particular community.

Cognitive Research in Science, Engineering and Education (IJCRSEE), Vol. 5 , 2017, No 2, pp. 1-18. 42. Slavova, V., K. Atanasov, A Generalized Net for Modeling Working Memory and Language Processing. – In: Proc. of the 7th International Conference Cognitive Modeling in linguistics, V. Text Processing and Cognitive Technologies, No 9, 2004, pp. 90-101. 43. Slavova, V., A. Soschen. A Fibonacci-Tree Model of Cognitive Processes Underlying Language Faculty. – In: Proc. of 3rd International Conference in Computer Science, NBU, University of Fulda, Boston University, 2007, pp

Abstract

Many works written by Klára Buzássyová from the 1970s onwards were devoted to the issues of contrastive research of languages. The study analyses the role of metonymy in speech acts expressing agreement in a contrastive perspective. The paper deals with linguistic variation of Slovak translation equivalents of English pragmatic marker fair enough in the exploitation of discoursive­illocutionary metonymy within indirect speech acts. It analyses data drawn from English­Slovak parallel corpus which form a translation paradigm of the given pragmatic marker. In a search for an explanation for usage of largely heterogeneous translation equivalents from various semantic­pragmatic fields, metonymy is pointed out as a central motivating factor. It functions on the basis of evocation of various aspects constituting the idealized cognitive model of agreement.

. 1991. Real patterns. Journal of Philosophy . 88: 27-51. Efron, B.; Tibshirani, R.J. 1993. An introduction to the bootstrap . New York: Chapman & Hall. Erev, I.; Ert, E.; Roth, A.; Haruvy, E.; Herzog, S.; Hau, R.; Hertwig, R.; Stewart, T.; West, R.; and Lebiere, C. 2010. A choice prediction competition for choices from experience and from description. Journal of Behavioral Decision Making: Special edition on Decisions from Experience . 23(1): 15-47. Gonzalez, C.; and Dutt, V. 2007. Learning to control a dynamic task: A system dynamics cognitive model of the slope

April 16, 2012, from http://www.ncld.org/ldbasics/ld-aamp-social-skills/social-aamp-emotionalchallenges/behavior-problemsand-learning-disabilities http://www.ncld.org/ldbasics/ld-aamp-social-skills/social-aamp-emotionalchallenges/behavior-problemsand-learning-disabilities Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research , 17(4), 460-469. Phillipson, S. (2011). When seeing is not believing: A cognitive therapeutic differentiationbetween conceptualizing and managing OCD. Retrieved