MIND & SOCIETY
Cognitive Studies in Economics and Social Sciences |
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| 2, 2007, Mind&Society, vol. 6 |
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Articles:
Ron Sun • Isaac Naveh
Social institution, cognition, and survival: A cognitive-social simulation”
Abstract
Although computational models of cognitive agents that incorpo-rate a wide range of cognitive functionalities have been developed in cognitive science, most of the work in social simulation still assumes rudimentary cognition on the part of the agents. In contrast, in this work, the interaction of cognition and social structures/processes is ex-plored, through simulating survival strategies of tribal societies.
The results of the simulation demonstrate interactions between cognitiv and social factors. For example, we show that cognitive capabilities and tendencies may be relevant to what social institutions may be adopted.
This work points to a cognitively based approach towards social simu-lation, as well as a new area of research-exploring the cognitive-social interaction through cognitively based social simulation.
Hiroshi Yama • Miwa Nishioka • Tomoko Horishita• Yayoi Kawasaki • Junichi Taniguchi
A dual process model for cultural differences in thought
Abstract
Nisbett et al. (2001) claim that East Asians are likely to use holistic thought to solve problems, whereas Westerners use analytic thought more, and discuss the differences in the frame of the individualism/collectivism distinction. The holistic versus analytic distinction has been the greatest point of interest of dual process theories, which imply that human thinking has two sub processes.
We apply a revised dual process model that proposes meme-acquired goals in both systems to explain cultural differences in thought. According to this, gene-installed goals are universal across cultures, whereas meme-acquired goals depend upon culture.
To introduce a dual process model means that we discuss adaptation both in terms of culture and natural selection. Hence, we propose an interactive view that supports an adaptive relation between mind and culture.
Antônio Gomes • Ricardo Gudwin • Charbel Niño El-Hani • João Queiroz
Towards the emergence of meaning processes in computers from Peircean semiotics
Abstract
In this work, we propose a computational approach to the triadic model of Peircean semiosis (meaning processes). We investigate theoretical constraints about the feasibility of simulated semiosis.
These constraints, which are basic requirements for the simulation of semiosis, refer to the synthesis of irreducible triadic relations (Sign – Object – Interpretant). We examine the internal organization of the triad S-O-I, that is, the relative position of its elements and how they relate to each other. We also suggest a multi-level approach based on self-organization principles.
In this context, semiosis is described as an emergent process. Nevertheless, the term ‘emergence’ is often used in a very informal way in the so called ‘emergent’ computation, without clear explanations and/or definitions.
In this paper, we discuss in some detail the meaning of the theoretical terms ‘emergence’ and ‘emergent’, showing how such an analysis can lead to improvements of the algorithm proposed.
Eliano Pessa • Graziano Terenzi
Semiosis in cognitive systema: A neural approach to the problem of meaning
Abstract
This paper deals with the problem of understanding semiosis and meaning in cognitive systems. To this aim we argue for a unified two-factor account according to which both external and internal information are non-independent aspects of meaning, thus contributing as a whole in determining its nature.
To overcome the difficulties stemming from this approach we put forward a theoretical scheme based on the definition of a suitable representation space endowed with a set of transformations, and we show how it can be implemented, in the case of a single agent, by a neural network architecture. Numerical experiments conducted on different instances of the latter show that similar representations are developed as a consequence of the fact that these instances are facing a similar semantic task.
This allows to model social and environmental influences through a system of interacting agents, each described by a specific implementation of this model architecture.
Andrea Pozzali
Can tacit knowledge fit into a computer model of scientific cognitive processes? The case of biotechnology.
Abstract
This paper tries to express a critical point of view on the computational turn in philosophy by looking at a specific field of study: philosophy of science. The paper starts by briefly discussing the main contributions that information and communication technologies have given to the rising of computational philosophy of science, and in particular to the cognitive modelling approach.
The main question then arises, concerning how computational models can cope with the presence of tacit knowledge in science.
Would it be possible to develop new ways of handling this specific type of knowledge, in order to incorporate it in computational models of scientific thinking? Or should tacit knowledge lead us to other approaches in using computer sciences to model scientific cognition? These questions are addressed by making reference to a detailed case study of a recent innovation development in the field of biotechnology.
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