Pritam Dutta, M.Optom, FAAO

Chandraprabha Eye Hospital, Assam, India



The term “cognitive science” today refers to the study of all aspects of the mind and encompasses a wide range of academic disciplines such as linguistics, anthropology, artificial intelligence (AI), philosophy, education, and neuroscience. Cognitive scientists focus on how the central nervous system processes, transforms and represents information as they research behaviour as well as intelligence.(1) The goal of cognitive science is to comprehend the fundamentals of intelligence so that an improved understanding of the mind and learning can be enabled.(1) Additionally, artificial intelligence (AI) is a computerised system’s mimics human intelligence. This made it possible to gather knowledge and use applicable laws to get a firm judgment so that self-correction might be encouraged. Previous and current trends in cognition and AI include SOAR architecture, ACT-R (Adaptive Control of Thought-Rational) and Stimulating creativity. ‘Table 1’

Table 1: Trends in cognitive science and AI

SOAR Architecture(2,3) In order to encourage in-person collaboration and communication, SOAR has also made it possible to stimulate virtual humans. The criticism of this application is that it is only appropriate for the virtual world, despite the fact that it integrates natural language understanding, emotion, action, and bodily control skills. It is still unclear whether certain psychological concepts need to be minimized in order to provide a more accurate approximation of the knowledge level of symbol processing. This is so that a better symbol system can be produced using the SOAR architecture, which aims to mimic the evolutionary design process.
ACT-R (adaptive control of thought-rational)(4) A computer simulation called ACT-R tries to define fundamental and nonreducible perceptual and cognitive activities. Therefore, ACT-R may be seen as a mechanism to determine how a human brain can be set up to handle cognitive production modules. The computational implementation of a unique code language is the foundation of this cognitive architecture. To gain access as an ACT-R interpreter, the researcher would need to download the ACRT-R code and load it into a Common Lisp distribution. Automatic step-by-step simulations of human behaviour are likely to be produced. Along with visual and aural encoding, cognitive processes like memory encoding and mental image manipulation can also be taken into consideration.
Stimulating creativity(5) There are three different sorts of creativity: artistic, abstract, and concrete. In order to communicate with people and encourage creativity, for instance, AI enables informed creative judgments rather than trying to duplicate the human intellect. The increasing usage of AI to improve human capacities has guaranteed exceptional creativity and helped the human mind in a way that makes achieving greater results quickly conceivable. The age of man versus machine is now a reality because routine tasks that used to require human involvement are now carried out automatically. For instance, conducting interviews or providing presentations to clients no longer necessitates the physical presence of people.

In addition, it is believed that all individuals would be aware of the fundamental aims of cognitive research, particularly the processes through which brain development of intelligence and creativity occurs. Improvements in learning techniques may result from a better understanding of the human brain’s learning process, which includes information retrieval. (6) Therefore; this human progress has the potential to be applied in classrooms where students’ minds or brains are just beginning to learn new things. In a similar vein, doing so would emphasize the development of medical remedies for people living with brain trauma and bring about beneficial improvements in existing theories. The following are some notable uses of cognitive science in artificial intelligence ‘Figure 1’ The future of human brain simulation is predicted to involve the development of nanotechnology, which aims to increase the speed and memory of computational hardware.(7) Cognitive and psychological research advancements have made it possible to study human behaviour in a variety of ways, opening the door for the development of intelligent entities.(8)


Therefore, it can be said that AI is a beneficial research tool in cognitive science, as this technological advancement facilitated a better understanding of the human mind. AI-based applications like speech-to-text, text-to-speech, natural language comprehension, and personalizer have enabled useful insights into human recognition. Additionally, it is predicted that intelligence agents will improve their capacity for simulating the human brain. However, there are several problems that may limit the application of brain simulation, which is why advancements like nanotechnology and theories from cognitive science and artificial intelligence are desired. These theories would specifically permit a thorough knowledge of the human mind in addition to accounting for complex issues.



  1. Collins, A., Bobrow, D.G. (Eds.): ‘Representation and understanding: studies in cognitive science’ ( Elsevier, Amsterdam, Netherlands, 2019), pp. 131–146
  2. Luber, S.: ‘Cognitive science artificial intelligence: simulating the human mind to achieve goals’. 2011 3rd Int. Conf. on Computer Research and Development, Shanghai, China, March 2011, vol. 1, pp. 207–210
  3. Vandierendonck, A.: ‘A working memory system with distributed executive control’, Perspect. Psychol. Sci., 2016, 11, (1), pp. 74–100
  4. Pentecost, D., Sennersten, C., Ollington, R., et al.: ‘Predictive ACT-R (PACT-R): using a physics engine and simulation for physical prediction in a cognitive architecture’. 8th Int. Conf. on Advanced Cognitive Technologies and Applications, Rome, Italy, December 2016, pp. 22–32
  5. Indurkhya, B.: ‘On the role of computers in creativity-support systems’, in ‘Knowledge, information and creativity support systems: recent trends, advances and solutions’ ( Springer, Cham, 2016), pp. 213–227
  6. Beaty, R.E., Kaufman, S.B., Benedek, M., et al.: ‘Personality and complex brain networks: the role of openness to experience in default network efficiency’, Hum. Brain Mapp., 2016, 37, (2), pp. 773–779
  7. Di Nuovo, A., Varrasi, S., Conti, D., et al.: ‘Usability evaluation of a robotic system for cognitive testing’. 2019 14th ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI), Daegu, Korea, March 2019, pp. 588–589
  8. Arora, M.R., Sharma, J., Mali, U., et al.: ‘Microsoft cognitive services’, Int. J. Eng. Sci., 2018, 8, (4), p. 17323