Titarenko I.N.

Southern Federal University, Russia

Multidisciplinary cognitive approaches in modern science

The present stage of scientific development is characterized by a number of specific features, among which should be mentioned significant increase in the role of technical sciences and engineering activities in the system of scientific knowledge. Till the middle of the last century the relevant sections of technical knowledge were seen as application to the basic science. Later the theoretical basis of technical knowledge was actively shaped. It led to the formation of relatively independent number of theories (radioelectronics, telemechanics, systems engineering, applied informatics) and the division into fundamental and applied technical knowledge. The orientation of modern science to the interests of social production is enhancing the role of technical knowledge and engineering activities. It led to the current level of science development which is often called technoscience. The term technoscience was introduced in the 70-s of the past century by J. Hottua and is widely used nowdays by specialists in different branches of scientific knowledge. The phenomenon of technoscience as a "specifically modern phenomenon" is still poorly studied [Barnes 2005:142-165]. Methods for studying technoscience are still being formed [Nowotny, Scott, Gibbons 2001: 35-39; Hottois 2004: 14-16; Yudin, 2010: 45-57]. It requires the philosophy to study the problems of the methodology which is applicable in modern technoscience and, which is defined by its characteristics.

Technoscience as a new stage in the development of science and technology is characterized not only by increasing the role of technical knowledge and engineering activities, but also by the fact that it changes the relationship between the branches of the sciences and the degree of their mutual influence. For example, engineering sciences and engineering were originally closely related to mathematics and natural science. At present they are more and more dependent on cognitive sciences. Activities on the design and modeling of human-machine systems, the development of intelligent information systems, automated systems for biology and medicine, which are of top-priority areas of research are impossible without close connection with cognitive sciences (philosophy of mind, cognitive psychology, cognitive linguistics, cognitive anthropology, and others). It is no mere chance that there are more and more appeal to the works of philosophers, anthropologists, psychologists, linguists in technical literature on robotics, artificial intelligence, sociotechnical design. For example, G. Luger and W. Stubblefield solving the problems of the development of artificial Intelligent Systems analyze the ideas of Plato, Aristotle, Hobbes, Descartes, Leibniz, Hume, Kant, Husserl, Gadamer and other thinkers [Luger, Stubblefield, 2005]. In the articles on the problems of humanoid robots control L.A. Stankevitch uses psychological models [Stankevitch, 2008]. A.G.Teslinov uses bipolar model of Yin-Yang logic [Teslinov, 1998], developing the management system, and many others. In the discourse of technical questions not only the results of cognitive research are used but also valuable historical and scientific tradition. Connection with cognitive science is observed while considering such problems as knowledge representation, artificial languages, machine learning, natural language understanding and semantic modeling, automated reasoning, nonverbal communicative interaction, attractor networks, etc.

Logical and epistemological, methodological and axiological problems in cognitive science have a direct impact on the design of complex technical systems and information technology due to close interrelationship and interdependence of cognitive sciences, engineering. For example, the problem of machine learning in artificial intelligent systems is directly dependent on the resolution of questions about whether it is possible to develop reliable methods of understanding and formalization of data about the experience of consciousness; what methods to use to describe the physical and technical term; to find out the relation of conscious and unconscious processes in sensory perception, memory, learning; whether there is a priori element in knowledge (philosophy of mind); to figure out human sensory perception, different types of storage media; whether it is possible to build mental models of memory functioning (cognitive psychology); the role of cultural aspects of thinking, internal conceptual systems that govern the behavior of a real person; to define the structure of the worldview (cognitive anthropology), the essence of the processes of understanding the natural language, the characteristics of learning and information processing, the principles of linguistic categorization (cognitive linguistics).

These questions and some others are being studied within the framework of the artificial intelligence as an interdisciplinary area of cognitive science (A. Newell, H.Simon, G. Luger, S. Russell, P. Norvig, F. Brooks, T.Winograd, J. McCarthy, J.Holland, V. Tarasov, D. Pospelov, P. Anokhin, E. Popov, and others); cognitive linguistics (J. Lakoff, R. Langacker, Y. Apresyan, A. Zalevskaya, A. Kibrik, I.Kobozeva, etc.); cognitive psychology (J. Bruner, J. Fodor, J. Broadbent, J.Anderson, R. Solso, B. Velichkovsky, V. Allakhverdov, W. Kosinski, and others); cognitive anthropology (R. Redfield, M. Cole, R. Casson, D. Holland, R. D'Andrade, J. Keller, and others).

Cognitive science is developing rapidly. The number of researches is constantly increasing and is classified as cognitive due to their specific subject area, methodology and terminology. Thousands of foreign scientific publications have already appeared on this subject over the past few decades, international scientific communities were formed (Cognitive Science Society, Hellenic Cognitive Science Society etc.), international forums are organized (European Cognitive Science Conference, 2003; European Conference on Cognitive Science (ECCS) – 1995, 1997, 1999, 2001, 2003, 2005, 2007, 2009 etc.). Russia is also interested in cognitive studies. There appeared Interregional Association of Cognitive Studies, The Center for cognitive programs and technologies of RSHU (Russian State Humanitarian University) and others. Conferences on cognitive science are regularly held (International Conference on Cognitive Science – Kazan, 2004, St. Petersburg, 2006; Moscow, 2008, Tomsk, 2010; conference on "Philosophy of Mind: Past and Present; Gryaznovskie reading" – Moscow, 2003, 2005, 2009; National Interdisciplinary Conference "Philosophy of Artificial Intelligence", Moscow, 2005, 2007, 2009; RSNE-NBIK-2011 – Moscow, 2011; Russian Scientific Conference "Neuroinformatics", etc.). Such active cognitive researches are caused by abundance of cognitive tasks which are formulated in the process of engineering activities. On the other hand, in the cognitive sciences are widely used techniques associated with technical sciences and computer science. It happens while studying the analysis of model-character, modular, neural network approach used in cognitive sciences.

Particular qualities of technoscience are the reasons to consider cognitive sciences, engineering sciences, engineering and technology activities which are the part of the processes of social development as integrity. They cause the necessity of interdisciplinary cognitive approaches to solve technoscience problems. The development of intelligent information systems, human-machine systems need a complex connection of philosophical ideas, cognitive, technical, engineering knowledge. In its turn it demands a dialogue between different scientific disciplines. Interdisciplinary approach completely corresponds the features of the current level of scientific knowledge and complex subjects of technoscience studies. Russian philosopher V. S. Stepin notes that in a lot of situations the development of complex self-developing systems is carried out as an interdisciplinary study in which the actions of specialists in one discipline are complemented by the work of heterogeneous (in terms of scientific specialization of the research) communities [Stepin 2010: 73-74].

For example, the interdisciplinary cognitive approach can be very productive in such top direction of the technoscience development as intelligent information systems that make up an essential element of the modern human-technical systems, information and telecommunication technologies, complex control systems, and space transportation systems and other intelligent information systems. Modelling of the intelligent information systems is one of the most promising and rapidly developing scientific and applied areas of computer science, which develops systems to support human activities, including word-processing problems in natural language, knowledge and knowledge bases modeling, knowledge management, pattern recognition, neurotechnology, internet intellectualization, conceptual programming, etc. The development of intelligent information systems includes cognitive interdisciplinary research aimed at understanding the processes of consciousness, memory, learning experience. This is due to the necessity of the development of the intelligent information systems and technologies to improve decision making in problematic situations. Any of these situations (from social conflict to the choice of the route) is described as a cognitive model (cognitive scheme, frame, archetype, etc.) Consequently, interdisciplinary cognitive approach and success in the field of cognitive studies are essential for the development of intelligent information technologies and systems.

Interdisciplinary cognitive approach can enhance the cognitive capabilities of various methods used in various branches of modern technoscience. Such interdisciplinary approaches correspond the world-class research in the field of philosophy, cognitive science, technical knowledge and engineering activities.

Literature:

1. Luger G. F. & Stubblefield W. A., Artificial Intelligence – Structures and Strategies for Complex Problem Solving. 5th edition. New York, NY: Addison Wesley, 2005.

2. Stankevitch L.A., Cognitive approach to robotic control systems design // Когнитивные исследования (Cognitive researches). 2008. №2. – P. 276-292.

3. Stepin V. S., Science and philosophy // Вопросы философии (Voprosy filosofii). 2010. №8. – P. 58-75; P. 73-74.

4. Teslinov A.G., Development of control systems: methodology and conceptual structures. М, 1998. –381 pp.

5. Yudin B.G., Science in the society of knowledge in a society of knowledge // Вопросы философии (Voprosy filosofii). 2010. №8. P. 45-57.

6. Barnes B., Elusive Memories of Technoscience // Perspectives on Science: Historical, Philosophical, Social. 2005. Vol. 13. Issue 2 (Technoscientific Productivity), Summer 2005. P. 142-165.

7. Hottois G. Techno-sciences and ethics // Agazzi E. Right, Wrong and Science. Ed. by Craig Dilworth. Poznań Studies in the Philosophy of Science and Humanities, Vol. 81. Amsterdam-NY, 2004. – 328 pp.

8. Nowotny H., Scott P., Gibbons M. Re-Thinking Science. Knowledge and the Public in an Age of Uncertainty. London, 2001. – 227 pp.