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Solution Generation through Hybrid Intelligence and Creativity based on Investment Portfolio

Volume 14, Number 7, July 2018, pp. 1641-1650
DOI: 10.23940/ijpe.18.07.p29.16411650

Qinyun Liua, Hua Zhoub, Hongji Yangc, and William Cheng Chung Chud

aCentre for Creative Computing, Bath Spa University, Bath, England
bCollege of Big Data and Intelligence Engineering, Southwest Forestry University, Kunming, 650000, China
cDepartment of Informatics, University of Leicester, Leicester, England
dDepartment of Computer Science, Tunghai University, Taiwan, China

(Submitted on April 16, 2018; Revised on May 19, 2018; Accepted on June 16, 2018)

Abstract:

Artificial Intelligence (AI) has been developed to be robust on computing. Learning can be achieved by connecting to heterogeneous data using AI algorithms, such as the Artificial Neural Network. Knowledge can be learned, and rules in the database can be discovered by machines through heuristic algorithms. However, creativity has not been achieved by computers like the human brain by using AI algorithms individually. This research serves to explore a method to achieve creative solution generation by utilizing a relationship between intelligence and creativity, assuming intelligence is the subset of creativity. Under this relationship, the computing can be fulfilled using AI algorithms. The theories of achieving creativity is the guidance of this method.

 

References: 32

          1. R. Sternberg and T. Lubart, Defying the Crowd: Cultivating Creativity in a Culture of Conformity, Free Press, American Psychological Association, New York, USA, 1995.
          2. R. Sternberg, Successful Intelligence, First Agency Publishing, American Psychological Association, New York, USA, 1997.
          3. R. Sternberg, Beyond IQ: A Triarchic Theory of Human Intelligence, Cambridge University Press, Press Syndicate of University of Cambridge, Cambridge, UK, 1985.
          4. R. Sternberg, The Triarchic Mind: A New Theory of Human Intelligence, Viking Press, New York, USA, 1988.
          5. R. Cattell, "Theory of Fluid and Crystallized Intelligence: A Critical Experiment", Journal of Educational Psychology, American Psychological Association, New York, USA, vol. 54, no. 1, pp. 1-8, 1963.
          6. R. Cattell, "Theory of Fluid and Crystallized Intelligence: A Critical Experiment", Journal of Educational Psychology, American Psychological Association, New York, USA, vol. 54, no. 1, 1963.
          7. R. Sternberg, and T. Lubart, "Investing in Creativity", American Psychologist, American Psychological Association, New York, USA, vol. 51, no. 7, p. 677, 1996.
          8. R. Sternberg, "Implicit Theories of Intelligence, Creativity, and Wisdom", Journal of Personality and Social Psychology, American Psychological Association, Washington, USA, vol. 49, no. 3, p. 607, 1985.
          9. I. Smith, "IQ, Creativity, and the Taxonomy of Educational Objectives: Cognitive Domain", Journal of Experimental Education, Taylor and Francis Co., London, UK, vol. 38, no. 4, pp.58-60, 1970.
          10. I. Smith, "IQ, Creativity, and Achievement: Interaction and Threshold", Multivariate Behavioural Research, American Psychological Association, New York, USA, vol. 6, no. 1, pp. 51-62, 1971.
          11. M. Boden, “Creativity and Artificial Intelligence”, Artificial Intelligence, Elsevier, Netherland, vol. 103, no. 1-2, pp. 347-356, 1998.
          12. P. Heermann and K. Nahid, "Classification of Multispectral Remote Sensing Data Using a Back-Propagation Neural Network", IEEE Transactions on Geoscience and Remote Sensing, London, UK, vol. 30, no. 1, pp. 81-88, 1992.
          13. T. Lee, "Back-Propagation Neural Network for Long-Term Tidal Predictions", Ocean Engineering, Elsevier, New York, USA, vol. 31, no. 2, pp. 225-238, 2004.
          14. S. Haykin, “A Comprehensive Foundation”, IEEE Neural Networks, London, UK, vol. 2, no., p. 41, 2004.
          15. M. Hagan, B. Howard and H. Mark, Neural Network Design, Boston PWS Publishing, Boston, USA, vol. 20, 1996.
          16. T. Berners-Lee, H. James and L. Ora, "The Semantic Web", Scientific American, Natural American Inc., USA, vol. 284, no. 5, pp. 34-43, 2001.
          17. S. Nigel, T. Berners-Lee and W. Hall, "The Semantic Web Revisited", IEEE Intelligent Systems, New York, USA, vol. 21, no. 3, pp. 96-101, 2006.
          18. S. Bechhofer, "OWL: Web Ontology Language", Encyclopedia of Database Systems, Springer, New York, USA, pp. 2008-2009, 2009.
          19. A, Bernstein, H. James, and N. Natalya, "A New Look at the Semantic Web", Communications of the ACM, New York, USA, vol. 59, no. 9, pp. 35-37, 2016.
          20. D. Allemang and H. James, Semantic Web for the Working Ontologist: Effective Modelling in RDFS and OWL, Elsevier, New York, USA, 2011.
          21. L. Zhang, and H. Yang, "Definition, Research Scope and Challenges of Creative Computing", 19th IEEE International Conference on Automation and Computing (ICAC), London, UK, pp. 1-6, 2013.
          22. A. Hugill and H. Yang, "The Creative Turn: New Challenges for Computing", International Journal of Creative Computing (IJCrC), Inderscience Enterprises Ltd., Olney, UK, vol. 1, no. 1, pp. 4-19, 2013.
          23. W. Schoenmakers and G. Duysters, "The Technological Origins of Radical Inventions", Research Policy, Elsevier, The Netherlands, vol. 39, pp. 1051-1059, 2010.
          24. H. Yang, D. Jing, and L. Zhang, "Creative Computing: An Approach to Knowledge Combination for Creativity?", IEEE Symposium on Service-Oriented System Engineering (SOSE), London, UK, pp. 407-414, 2016.
          25. L. Zou, Q. Liu, C. Zhang and H. Yang, "An Approach to Applying Creative Computing in Tourism by Constructing a Big Data based Knowledge System Framework", 22nd IEEE International Conference on Automation and Computing (ICAC), London, UK, pp. 244-249, 2016.
          26. D. Jing, and H. Yang, "Creative Computing for Bespoke Ideation", 39th IEEE Computer Software and Applications Conference (COMPSAC), Taichung, Taiwan, China, vol. 1, pp. 34-43, 2015.
          27. L. Zhang and H. Yang, "Knowledge Discovery in Creative Computing for Creative Tasks", Creativity in Intelligent Technologies and Data Science: First Conference(CIT&DS), Springer, London, UK, vol. 535, p. 93, 2015.
          28. J. Perkins, Python 3 Text Processing with NLTK 3 Cookbook, Packt Publishing Ltd, Birmingham, UK, 2014.
          29. X. Wu, et al, "Top 10 Algorithms in Data Mining", Knowledge and Information Systems, Springer, London, UK, vol. 14, no. 1, pp. 1-37, 2008.
          30. M. Al-Maolegi and A. Bassam, "An Improved Apriori Algorithm for Association Rules", ArXiv.org., Cornell University Library, USA, 2014.
          31. J. Dongre, L. Gend and S. V. Tokekar, "The Role of Apriori Algorithm for Finding the Association Rules in Data Mining”, IEEE International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT), India, 2014.
          32. W. Schoenmakers, and G. Duysters, "The Technological Origins of Radical Inventions", Research Policy, Elsevier, The Netherlands, vol. 39, pp. 1051-1059, 2010.

                   

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