Skip to main content

Artificial Intelligence and Algorithms in Intelligent Systems

Advanced Analytics: Moving Forward Artificial Intelligence (AI), Algorithm Intelligent Systems (AIS) and General Impressions from the Field

  • Conference paper
  • First Online:
Artificial Intelligence and Algorithms in Intelligent Systems (CSOC2018 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 764))

Included in the following conference series:

Abstract

The possibility of creating thinking systems discusses issues that may arise in the near future of AI. However this outlines challenges to ensure that AI operates safely as it approaches humans in its intelligence from Algorithms Intelligent Systems. To understand how progress may proceed we need to understand how existing algorithms are developed and improve, differentiating the concepts between data analytics and data algorithmic decision making. This article reviews the literature on AI and AIS and presents some general guidelines and a brief summary of research progress and open research questions. The first section reviews the basic foundation of Artificial Intelligence to provide a common basis for further discussions and the second section of this paper suggests the development of Algorithm Intelligence Systems models including: learning algorithms such as learning from observations, learning in Neural and Belief Networks and reinforcement learning.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Nilsson, N.J.: Artificial Intelligence: A New Synthesis. Morgan Kaufmann Publishers Inc., San Francisco (1998)

    MATH  Google Scholar 

  2. Carter, M.: Minds and computers: an introduction to the philosophy of artificial intelligence. Hist. Philos. Log. 30(3), 306–308 (2009)

    Article  MathSciNet  Google Scholar 

  3. Feigenbaum, J., Feldman, E.A.: Computers and Thought. McGraw Hill, New York (1963)

    Google Scholar 

  4. Bransford, J.D., Brown, A.L., Cocking, R.R.: How People Learn: Brain, Mind, Experience, and School. National Academy Press, Washington (1999)

    Google Scholar 

  5. Gardner, H.: Multiple Intelligences: The Theory in Practice. McGraw Hill, New York (1993)

    Google Scholar 

  6. Sternberg, R.: The Triarchic Mind: A New Theory of Human Intelligence. Penguin Books, New York (1988)

    Google Scholar 

  7. Etzioni, D., Weld, O.: A softbot-based interface to the internet. Commun. ACM 37(7), 72–76 (2005)

    Article  Google Scholar 

  8. Turing, A.M.: Computing machinery and intelligence. Mind 59, 433–460 (1950)

    Article  MathSciNet  Google Scholar 

  9. Salamon, A., Muehlhauser, L.: Intelligence explosion: evidence and import. In: Eden, A., Moor, J., Søraker, J., Steinhart, E. (eds.) Singularity Hypotheses. The Frontiers Collection. Springer, Heidelberg (2012)

    Google Scholar 

  10. Soares, N., Fallenstein, B.: Agent foundations for aligning machine intelligence with human interests: a technical research agenda. Technol. Singul. Manag. Journey, pp. 1–14 (2017)

    Google Scholar 

  11. Holtzman, S.: Intelligent Decision Systems. Addison-Wesley Publishing Company, New York (1989)

    Google Scholar 

  12. Howard, R.A.: The foundations of decision analysis. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 4, 211–219 (1968)

    Article  Google Scholar 

  13. Matheson, R.A., Howard, J.E.: Readings on the Principles and Applications of Decision Analysis, pp. 445–475. Strategic Decisions Group, California (1967)

    Google Scholar 

  14. Aho, A.V., Hopcroft, J.E., Ullman, J.D.: Data Structures and Algorithms. Addison-Wesley Publishing Company, California (1983)

    Google Scholar 

  15. Gama, J., Carvalho, A.P.L., Faceli, K., Lorena, A.C., Oliveira, M.: Extracçao de conhecimento de dados, 2nd edn. Silabo, Lisboa (2015)

    Google Scholar 

  16. Maimon, O., Rokach, L.: The Data Mining and Knowledge Discovery Handbook. TEL-AVIV University of Israel, Israel (2005)

    Google Scholar 

  17. Han, J., Kamber, M., Pei, J.: Data Mining Concepts and Techiques. Elsevier, New York (2012)

    MATH  Google Scholar 

  18. De Coninck, N.: The relationship between big data analytics and operations research. Universiteit Gent (2017)

    Google Scholar 

  19. Kolmogoroff, A.: Foundations of the Theory of Probability. Chelsea Publishing Co., New York (1959)

    MATH  Google Scholar 

  20. Lawrence, P., Andriola, J.: Three-step method evaluates neural networks for your application. In: EDN, pp. 93–100 (1992)

    Google Scholar 

  21. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules in large databases. In: Proceedings of the 20th International Conference on Very Large Data Bases, pp. 487–499 (1994)

    Google Scholar 

  22. Han, R., Pei, J., Yin, J., Mao, Y.: Mining frequents patterns without candidate generation. Data Min. Knowl. Disc. 8, 53–87 (2004)

    Google Scholar 

  23. Tomasik, B.: Artificial Intelligence and its implications for future suffering (2016)

    Google Scholar 

Download references

Acknowledgments

Thanks to our colleagues for the discussion and comments on various aspects of this research. We also want to thank to Center of Technology and systems – CTS in UNINOVA in Nova University in Lisbon for supporting this research.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Carla Sofia R. Silva .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Silva, C.S.R., Fonseca, J.M. (2019). Artificial Intelligence and Algorithms in Intelligent Systems. In: Silhavy, R. (eds) Artificial Intelligence and Algorithms in Intelligent Systems. CSOC2018 2018. Advances in Intelligent Systems and Computing, vol 764. Springer, Cham. https://doi.org/10.1007/978-3-319-91189-2_30

Download citation

Publish with us

Policies and ethics