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Embodying Intelligence in Autonomous and Robotic Systems with the Use of Cognitive Psychology and Motivation Theories

Abstrakt

The article discusses, on a certain level of abstraction and generalization, a coherent anthropological approach to the issue of controlling autonomous robots or agents. A contemporary idea can be based on appropriate modeling of the human mind using the available psychological knowledge. One of the main reasons for developing such projects is the lack of available and effective top-down approaches resulting from the known research on autonomous robotics. On the other hand, there is no system that models human psychology sufficiently well for the purpose of constructing autonomous systems. Nevertheless, to combat this lack, several ideas have been proposed for embodying human intelligence. We review recent progress in our understanding of the mechanisms of cognitive computations underlying decision-making and discuss some of the pertinent challenges identified and implemented in several systemic solutions founded on cognitive ideas (like LIDA, CLARION, SOAR, MANIC, DUAL, OpenCog). In particular, we highlight the idea of an Intelligent System of Decision-making (ISD) based on the achievements of cognitive psychology (using the aspect of ‘information path’), motivation theory (where the needs and emotions serve as the main drives, or motivations, in the mechanism of governing autonomous systems), and several other detailed theories, which concern memory, categorization, perception, and decision-making. In the ISD system, in particular, an xEmotion subsystem covers the psychological theories on emotions, including the appraisal, evolutionary and somatic theories.

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Informacje szczegółowe

Kategoria:
Publikacja monograficzna
Typ:
rozdział, artykuł w książce - dziele zbiorowym /podręczniku w języku o zasięgu międzynarodowym
Tytuł wydania:
Advances in Data Analysis with Computational Intelligence Methods strony 335 - 352
Język:
angielski
Rok wydania:
2018
Opis bibliograficzny:
Kowalczuk Z., Czubenko M.: Embodying Intelligence in Autonomous and Robotic Systems with the Use of Cognitive Psychology and Motivation Theories// Advances in Data Analysis with Computational Intelligence Methods/ ed. Gawęda A.E., Kacprzyk J., Rutkowski L., Yen G. Cham: , 2018, s.335-352
DOI:
Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1007/978-3-319-67946-4_15
Bibliografia: test
  1. Agarwal, M., Goel, S.: Expert system and its requirement engineering process. In: International Conference on Recent Advances and Innovations in Engineering. pp. 1-4. IEEE (2014) otwiera się w nowej karcie
  2. Alsop, S.: Beyond Cartesian Dualism: Encountering Affect in the Teaching and Learning of Science., vol. 26. Springer Science & Business Media (2005) otwiera się w nowej karcie
  3. Anderson, M.L.: Embodied Cognition: A field guide. Artificial Intelligence 149(1), 91-130 (2003) otwiera się w nowej karcie
  4. Arkin, R.C.: Behavior-Based Robotics. MIT Press, Cambridge, MA (1998)
  5. Bennett, C.C., Doub, T.W.: Artificial Intelligence in Behavioral and Mental Health Care. In: Luxton, D.D. (ed.) Artificial Intelligence in Behavioral and Mental Health Care, chap. 2, pp. 27-51. Elsevier (2016) otwiera się w nowej karcie
  6. Brim, N., Orville, G., Glass, D.C.: Personality and Decision Processes: Studies in the Social Psychology of Thinking. Stanford University Press (1962)
  7. Brooks, R.A.: Intelligence without reason. In: International Joint Conference on Artificial Intelligence. pp. 569-595. Sydney (1991) otwiera się w nowej karcie
  8. Brooks, R.A.: Intelligence without representation. Artificial Intelligence 47(1-3), 139-159 (1991) otwiera się w nowej karcie
  9. Chen, W., Qu, T., Zhou, Y., Weng, K., Wang, G., Fu, G.: Door recognition and deep learning algorithm for visual based robot navigation. In: IEEE International Conference on Robotics and Biomimetics. pp. 1793-1798. IEEE (2014) otwiera się w nowej karcie
  10. Chown, E., Jones, R., Henninger, A.: An architecture for emotional decision- making agents. In: Proceedings of the first international joint conference on Au- tonomous agents and multiagent systems: part 1. pp. 352-353. ACM, Bologna (2002) otwiera się w nowej karcie
  11. Coward, L., Sun, R.: Criteria for an effective theory of consciousness and some preliminary attempts. Consciousness and Cognition 13(2), 268-301 (2004) otwiera się w nowej karcie
  12. Czubenko, M., Ordys, A., Kowalczuk, Z.: Autonomous driver based on intelligent system of decision-making. Cognitive Computation 7(5), 569-581 (2015) otwiera się w nowej karcie
  13. Damjanovic, V., Kravcik, M., Devedzic, V.: eQ: an adaptive educational hypermedia-based BDI agent system for the semantic Web. In: Fifth IEEE In- ternational Conference on Advanced Learning Technologies. pp. 421-423. IEEE (2005) otwiera się w nowej karcie
  14. De Silva, L., Ekanayake, H.: Behavior-based robotics and the reactive paradigm a survey. In: International Conference on Computer and Information Technology. pp. 36-43. Khulna (2008)
  15. Dewey, J.: How we think. D.C. Heath & Company, Mineola, N.Y. (1910) otwiera się w nowej karcie
  16. Du, P., Liu, H.y.: Study on air combat tactics decision-making based on Bayesian networks. In: 2nd IEEE International Conference on Information Management and Engineering. pp. 252-256. IEEE, Chengdu (2010) otwiera się w nowej karcie
  17. Flemmer, R.C.: A scheme for an embodied artificial intelligence. In: 2009 4th In- ternational Conference on Autonomous Robots and Agents. pp. 1-9. IEEE (2010) otwiera się w nowej karcie
  18. Franklin, S., Madl, T., D'Mello, S., Snaider, J.: LIDA: A Systems-level Architecture for Cognition, Emotion, and Learning. IEEE Transactions on Autonomous Mental Development 6(1), 19-41 (2014) otwiera się w nowej karcie
  19. Goodwin, P., Wright, G.: Decision Analysis for Management Judgment. Wiley (2009)
  20. Gottfredson, L.: The general intelligence factor. Scientific American Presents 9(4), 24-29 (1998) otwiera się w nowej karcie
  21. Hernandez, A., El Fallah-Seghrouchni, A., Soldano, H.: Distributed learning in intentional BDI multi-agent systems. In: Proceedings of the Fifth Mexican Inter- national Conference in Computer Science. pp. 225-232. IEEE (2004)
  22. Herve, L.G., Sorin, M.: A model of cooperative agent based on imitation and Maslow's Pyramid of needs. In: International Joint Conference on Neural Networks. pp. 1229-1236. IEEE (2009) otwiera się w nowej karcie
  23. Ji, S., Yang, M., Yu, K.: 3D convolutional neural networks for human action recog- nition. IEEE Transactions on Pattern Analysis and Machine Intelligence 35(1), 221-31 (2013) otwiera się w nowej karcie
  24. Jones, R., Laird, J.: Constraints on the design of a high-level model of cognition. In: Proceedings of the Nineteenth Annual Conference of the Cognitive Science Society (1997)
  25. Korecko, S., Herich, T., Sobota, B.: JBdiEmo -OCC model based emotional engine for Jadex BDI agent system. In: 12th International Symposium on Applied Machine Intelligence and Informatics (SAMI). pp. 299-304. IEEE, Herl'any (2014) otwiera się w nowej karcie
  26. Kowalczuk, Z., Czubenko, M.: DICTOBOT an autonomous agent with the abil- ity to communicate. In: Zeszyty Naukowe Wydziału ETI Politechniki Gdańskiej. Technologie Informacyjne. pp. 87-92 (2010) otwiera się w nowej karcie
  27. Kowalczuk, Z., Czubenko, M.: Interactive cognitive-behavioural decision making system. In: Rutkowski, L. (ed.) Artifical Intelligence and Soft Computing Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, vol. 6114 (II), pp. 516-523. Springer-Verlag, Berlin -Heidelberg -New York (2010) otwiera się w nowej karcie
  28. Kowalczuk, Z., Czubenko, M.: Model of human psychology for controlling au- tonomous robots. In: 15th International Conference on Methods and Models in Automation and Robotics. pp. 31-36 (2010) otwiera się w nowej karcie
  29. Kowalczuk, Z., Czubenko, M.: Intelligent Decision-Making System for Autonomous Robots. International Journal of Applied Mathematics and Computer Science 21(4), 621-635 (2011) otwiera się w nowej karcie
  30. Kowalczuk, Z., Czubenko, M.: xEmotion -a computational model of emotions ded- icated for intelligent decision-making systems, in Polish (xEmotion -obliczeniowy model emocji dedykowany dla inteligentnych systemów decyzyjnych). Pomiary, Au- tomatyka, Robotyka 2(17), 60-65 (2013) otwiera się w nowej karcie
  31. Kowalczuk, Z., Czubenko, M.: Cognitive Memory for Intelligent Systems of Decision-Making, Based on Human Psychology. In: Korbicz, J., Kowal, M. (eds.) Intelligent Systems in Technical and Medical Diagnostics, Advances in Intelligent Systems and Computing, vol. 230, chap. Cognitive, pp. 379-389. Springer Berlin Heidelberg (2014) otwiera się w nowej karcie
  32. Kowalczuk, Z., Czubenko, M.: Overview of humanoid robots, in Polish (Przegląd robotów humanoidalnych). Pomiary, Automatyka, Robotyka 19(4), 67-75 (2015) otwiera się w nowej karcie
  33. Kowalczuk, Z., Czubenko, M.: Computational Approaches to Modeling Artificial Emotion -An overview of the Proposed Solutions. Frontiers in Robotics and AI 3(21), 1-20 (2016) otwiera się w nowej karcie
  34. Kowalczuk, Z., Czubenko, M.: Interpretation and Modeling of Emotions for the Governance of Autonomous Agent-Robots with the Use of the Paradigm of Scheduling Variable Control (2016), in preparation otwiera się w nowej karcie
  35. Kowalczuk, Z., Czubenko, M., Jędruch, W.: Learning Processes in Autonomous Agents using an Intelligent System of Decision-making. In: Kowalczuk, Z. (ed.) Advances in Intelligent Systems and Computing, pp. 301-315. Springer, Berlin - Heidelberg -New York (2016) otwiera się w nowej karcie
  36. Laird, J.: The Soar cognitive architecture. MIT Press (2012) otwiera się w nowej karcie
  37. Laird, J.: Extending the Soar cognitive architecture. In: Wang, P., Goertzel, B., Franklin, S. (eds.) Proceedings of the Artificial General Intelligence. vol. 171, pp. 224-235. IOS Press (2008) otwiera się w nowej karcie
  38. Laird, J., Mohan, S.: A case study of knowledge integration across multiple mem- ories in Soar. Biologically Inspired Cognitive Architectures 8, 93-99 (2014) otwiera się w nowej karcie
  39. Laird, J.E., Newell, A., Rosenbloom, P.S.: SOAR: An architecture for general in- telligence. Artificial Intelligence 33(1), 1-64 (1987) otwiera się w nowej karcie
  40. Madl, T., Franklin, S.: Constrained incrementalist moral decision making for a biologically inspired cognitive architecture. In: Trappl, R. (ed.) A Construction Manual for Robots' Ethical Systems, pp. 137-153. Cognitive Technologies, Springer International Publishing (2015) otwiera się w nowej karcie
  41. Mann, L., Harmoni, R., Power, C.: The GOFER course in decision making. In: Brown, J., Brown, R. (eds.) Teaching decision making to adolescents. Routledge Taylor and Francis Group, New Jersey, London (1991) otwiera się w nowej karcie
  42. Marsella, S., Gratch, J., Petta, P.: Computational models of emotion. In: Scherer, K.R., Bänziger, T., Roesch, E.B. (eds.) A blueprint for affective computing: A sourcebook and manual, pp. 21-41. Oxford University Press, Oxford, UK (2010)
  43. Matsumoto, Y., Nishida, Y., Motomura, Y., Okawa, Y.: A Concept of Needs- Oriented Design and Evaluation of Assistive Robots Based on ICF. In: Interna- tional Conference on Rehabilitation Robotics. Zurich (2011) otwiera się w nowej karcie
  44. Mintzberg, H., Raisinghani, D., Théorêt, A.: The structure of 'unstructured' deci- sion processes. Administrative science quarterly 21(2), 246-275 (1976) otwiera się w nowej karcie
  45. Miwa, H., Itoh, K., Ito, D., Takanobu, H., Takanishi, A.: Introduction of the need model for humanoid robots to generate active behavior. In: IEEE/RSJ Interna- tional Conference on Intelligent Robots and Systems. vol. 2, pp. 1400-1406 (2003) otwiera się w nowej karcie
  46. Moravec, H.: Mind Children. The Future of Robot and Human Intelligence. Har- vard University Press (1988)
  47. Newell, A., Simon, H.A.: Human problem solving. Prentice-Hall, Englewood Cliffs (1972)
  48. Nielsen, P., Koss, F., Taylor, G., Jones, R.: Communication with intelligent agents. In: Proceedings of IITSEC. pp. 824-834. Orlando, FL (2000)
  49. Norvig, P.: On Chomsky and the two cultures of statistical learning. On-line essay in response to Chomsky's remarks . . . (2011) otwiera się w nowej karcie
  50. Novak, E.: Toward a mathematical model of motivation, volition, and performance. Computers & Education 74, 73-80 (2014) otwiera się w nowej karcie
  51. Paivio, A., Csapo, K.: Picture superiority in free recall: Imagery or dual coding? Cognitive Psychology 5(2), 176-206 (1973) otwiera się w nowej karcie
  52. Pan, Y.T., Tsai, M.S.: Development a BDI-Based Intelligent Agent Architecture for Distribution Systems Restoration Planning. In: 15th International Conference on Intelligent System Applications to Power Systems. pp. 1-6. IEEE, Curitiba (2009) otwiera się w nowej karcie
  53. Pickering, A.: The Cybernetic Brain. The University of Chicago Press (2011)
  54. Pijanowski, J.: The role of learning theory in building effective college ethics cur- ricula. Journal of College and Character 10(3), 1-14 (2009) otwiera się w nowej karcie
  55. Rasheed, N., Amin, S.H., Sultana, U., Shakoor, R., Zareen, N., Bhatti, A.R.: The- oretical accounts to practical models: Grounding phenomenon for abstract words in cognitive robots. Cognitive Systems Research 40, 86-98 (dec 2016) otwiera się w nowej karcie
  56. Ren, L., Liu, W., Liang, X.: The research on the needs model of the China net- work game. In: IEEE International Conference on Communications Technology and Applications. pp. 255-258. IEEE (2009)
  57. Seepanomwan, K., Caligiore, D., Cangelosi, A., Baldassarre, G.: Generalisation, decision making, and embodiment effects in mental rotation: A neurorobotic ar- chitecture tested with a humanoid robot. Neural Networks 72, 31-47 (2015) otwiera się w nowej karcie
  58. Simon, H.A.: The New Science of Managment Decision. Prentice Hall PTR (1960) otwiera się w nowej karcie
  59. Spearman, C.: "General Intelligence" objectively determined and measured. The American Journal of Psychology 15(2), 201-292 (1904) otwiera się w nowej karcie
  60. Starzyk, J.: Motivation in embodied intelligence (2008)
  61. Sternberg, R.J., Salter, W.: Handbook of Human Intelligence. Cambridge Univer- sity Press, UK: Cambridge (1982) otwiera się w nowej karcie
  62. Sun, R.: Moral judgment, human motivation, and neural networks. Cognitive Com- putation 5(4), 566-579 (2013) otwiera się w nowej karcie
  63. Sun, R., Helie, S.: Psychologically realistic cognitive agents: taking human cogni- tion seriously. Journal of Experimental & Theoretical Artificial Intelligence 25(1), 65-92 (2013) otwiera się w nowej karcie
  64. Sun, R., Merrill, E., Peterson, T.: From implicit skills to explicit knowledge: A bottom-up model of skill learning. Cognitive science 25(2), 203-244 (2001) otwiera się w nowej karcie
  65. Wang, L., Wang, M.: Modeling of combined Bayesian networks and cognitive frame- work for decision-making in C2. Journal of Systems Engineering and Electronics 21(5), 812-820 (2010) otwiera się w nowej karcie
  66. Żurada, J., Barski, M., Jędruch, W.: Artificial Neural Networks, in Polish (Sztuczne sieci neuronowe). Wydawnictwo naukowe PWN, Warszawa (1996)
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Politechnika Gdańska

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