Creativity as Cognitive design--论文代写范文精选

我们将使用适当的工具展示逻辑开放性,这些现象无法描述算法或正式的模型。创造力之间的相关性表明,开放模型是最好的方式，提供一个正式的定义。下面的paper代写范文介绍了不同的建模方法。

Abstract
Creativity is an open problem which has been differently approached by several disciplines since a long time. In this contribution we consider as creative the constructivist design an observer does on the description levels of complex phenomena, such as the self-organized and emergent ones ( e.g., Bènard rollers, Belousov-Zhabotinsky reactions, flocks, swarms, and more radical cognitive and social emergences). We consider this design as related to the Gestaltian creation of a language fit for representing natural processes and the observer in an integrated way. Organised systems, both artificial and most of the natural ones are designed/ modelled according to a logical closed model which masters all the inter-relation between their constitutive elements, and which can be described by an algorithm or a single formal model. 

We will show there that logical openness and DYSAM (Dynamical Usage of Models) are the proper tools for those phenomena which cannot be described by algorithms or by a single formal model. The strong correlation between emergence and creativity suggests that an open model is the best way to provide a formal definition of creativity. A specific application relates to the possibility to shape the emergence of Collective Behaviours. Different modelling approaches have been introduced, based on symbolic as well as sub-symbolic rules of interaction to simulate collective phenomena by means of computational emergence. Another approach is based on modelling collective phenomena as sequences of Multiple Systems established by percentages of conceptually interchangeable agents taking on the same roles at different times and different roles at the same time. 
Key-words: constructivist design, complex systems, dynamical usage of models, emergence, logical openness, mesoscopic variables, meta-structure

Introduction 
The observer’s cognitive system, - dynamic memory, image processing, high cognitive skills for input representations -, carries out a plurality of choices in the world description. It leads to the creation of languages to describe the possible representation states. In particular, in the scientific description of the Nature it is necessary to choose the proper description level as well as the significant variables in order to outline the behaviors of the system under consideration. Such kind of languages are thus a bridge between theory and praxis, a mind- world cognitive isomorphism according to Gestalt principles. 

For example, Bongard proposed an approach to visual pattern recognition where choosing a suitable language makes possible speaking about and describing an object (Arnheim, 1997; Bongard, 1970). Actions and rules effectively used in the world of the observer are used to carry out cognitive models. Our approach is close to those introduced to model and simulate creativity (Creativity Machines and Imagitron: Holmes,1996; Thaler, 1996a; 1996b,1994; 2005), with a further effort in the direction of intrinsic emergent phenomena (Licata, 2008a). The designing of intrinsically non observer-related erratic devices is a typical problem which can be handled by Meta-Structures (Minati, 2008a; 2009) and in dissipative quantum model of the brain (Vitiello, 2001; Minati and Vitiello, 2006). Differently from some disciplinary usages like in physics and logics, we will use the term coherence with the meaning of detecting emergence in collective interactions as the invariant properties in flocks and swarms. In other words, cognitive activity responds to the emergent patterns of coherence by constructive designing, so drawing out a shape from the world’s noise and entropy. 

Creativity and Emergence 
The problem to model creativity is a problem deeply connected to one of the central research topic of current research, i.e., emergence. Usually creativity is conceived as the ability to make emerging unusual cognitive strategies to deal with the complexity of the relation observer-observed. It is well-known how processes of emergence may be classified in two huge categories: a) Computational emergence, completely describable by a single formal model and by an algorithm; b) Intrinsic or radical emergence, non describable by a single formal model because of the dynamical complexity of interactions between system and environment. The latter, contrary to what generally assumed, is the simplest and most diffused in nature, e.g., phase transitions, folding protein , cognition, socio-economic processes, and so on, see, for instance, 3 (Licata, 2009). So, the problem of scientifically describing creativity finds its proper formulation within the approach to emergence. In particular, the key question is: once a process of intrinsic emergence -unforeseeable on the basis of any available model- has occurred, how can we analyse it, even partially, by computational tools? (Licata, 2008b). 

Let’s note that old Artificial Intelligence had tried and fared poorly in reducing creativity to an “algorithmic machinery”. What we are going to propose here is totally different. Without taking into consideration all the creativity aspects, we will focus on a specific problem: to fix the suitable variables in order to describe some significant features of highly complex systems. One of the greatest successes of theoretical physics at the end of the eighth centuries was the ability to find a connection between the microscopic and macroscopic representations of perfect gases thanks to the contributions introduced by Boltzmann, Maxwell and Gibbs. The study of mesoscopic systems was found much more difficult, because it is not always possible the identification of significant variables related to the dynamics of the Middle Way (Lauglin & Pines, 1999; Laughlin et al., 2000). In this case the more suitable cognitive strategy is to find step by step, on different spatial and temporal scales, the parameters able to allow a coherent representation of global aspects of the system. In this conceptual framework the term ‘coherent’ takes on a formal meaning only after the observer has selected a description level. In this sense the Meta-Structures project defines an approach to creativity based on the updating of models for complex systems as based on the cognitive design performed by the observer updating models used for complex systems.

Conclusions 
We presented the very strong, even definitional, relation between emergence and creativity. We discussed the subject with relation to the well-known Gestaltian topics introduced by Bongard, like its famous one hundred squares and his imitation and good continuation principles studied for visual pattern recognition in Artificial Intelligence. We introduced how the general problem may be theoretically dealt with by logical openness and the dynamic usage of models. We then presented the Meta-Structures project having the aim to model general coherence, like in Collective Behaviours, by using formal properties, i.e., Meta-Structures, trough suitable mesoscopic variables created by the observer as design, invention, good continuity and imitation, of the level of description. We presented possible lines of research for the generalisation of the approach under study that appears extremely rich in suggestions for the comprehension of both the world and cognitive processes.(paper代写)

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