Abstract
The 8th International Conference on Neural Network and Artificial Intelligence organizes a round table discussion where, thinking of the title of this conference ’neural network and artificial intelligence,’ we discuss whether we will be able to achieve a real human-like intelligence by using an artificial neural network, or not. This article is to break the ice of the session. We argue how these proposed machines, including those by neural networks, are intelligent, how we define machine intelligence, how can we measure it, how those measurements really represent an intelligence, and so on. For the purpose, we will take a brief look at a couple of formal definitions of machine intelligence so far proposed. We also take it a consideration on our own definition of machine intelligence.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Chaitin, G.J.: Gödel’s theorem and information. Theoretical Physics 21(12), 941–954 (1982)
Dreyfus, H.: What computers can’t do. MIT Press (1979)
Frosini, P.: Does intelligence imply contradiction? Cognitive Systems Research 10(4), 297–315 (2009)
Gnilomedov, I., Nikolenko, S.: Agent-based economic modeling with finite state machines. In: Combined Proceedings of the International Symposium on Social Network Analysis and Norms for MAS, pp. 28–33 (2010)
Goertzel, G.: Toward a formal characterization of real-world general intelligence. In: Proceedings of the 3rd International Conference on Artificial General Intelligence, pp. 19–24 (2011)
Hernández-Orallo, J.: Beyond the Turing test. Journal of Logic, Language and Information 9(4), 447–466 (2000)
Hernández-Orallo, J.: A (hopefully) non-biased universal environment class for measuring intelligence of biological and artificial systems. In: Proceedings of the 3rd International Conference on Artificial General Intelligence, pp. 182–183 (2010)
Hernández-Orallo, J., Dowe, D.L.: Measuring universal intelligence: Towards an anytime intelligence test. Artificial Intelligence 174(18), 1508–1539 (2010)
Hibbard, B.: Bias and no free lunch in formal measures of intelligence. Journal of Artificial General Intelligence 1, 54–61 (2009)
Hibbard, B.: Measuring agent intelligence via hierarchies of environments. In: Schmidhuber, J., Thórisson, K.R., Looks, M. (eds.) AGI 2011. LNCS, vol. 6830, pp. 303–308. Springer, Heidelberg (2011)
Hingston, P.: A Turing test for computer game bots. IEEE Transactions on Computational Intelligence and AI in Games 1(3), 169–186 (2009)
Legg, S., Hutter, M.: Universal intelligence: A definition of machine intelligence. Minds and Machines 17(4), 391–444 (2007)
Malkiel, B.G.: A random walk down wall street: The time-tested strategy for successful investing. W.W. Norton & Company (2007)
McCorduck, P.: Machines who think: A personal inquiry into the history and prospects of artificial intelligence. A.K. Peters Ltd. (2004)
Michie, D.: Turing’s test and conscious thought. Artificial Intelligence 60, 1–22 (1993)
Smith, W.D.: Mathematical definition of intelligence (and consequences) (2006), http://math.temple.edu/wds/homepage/works.html
Solomonoff, R.J.: A formal theory of inductive inference: Parts 1 and 2. Information and Control 7, 1–22, 224–254 (1964)
Standage, T.: The Turk: The life and times of the famous eighteenth-century chess-playing machine. Walker & Company (2002)
Turing, A.M.: Computing machinery and intelligence. Mind 59(236), 433–460, http://www.loebner.net/Prizef/TuringArticle.html
Turing, A.M.: Intelligent machinery (1948), See, e.g., Copeland, B.J.: The essential Turing: The ideas that gave birth to the computer age. Clarendon Press, Oxford (2004)
Weng, J.: Connectionists Digest 335(4), 12 (2013)
Wolpert, D., Macready, W.: No free lunch theorems for optimization. IEEE Transactions on Evolutionary Computation 1, 67–82 (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Imada, A. (2014). Can Artiticial Neural Networks Evolve to be Intelligent Like Human?. In: Golovko, V., Imada, A. (eds) Neural Networks and Artificial Intelligence. ICNNAI 2014. Communications in Computer and Information Science, vol 440. Springer, Cham. https://doi.org/10.1007/978-3-319-08201-1_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-08201-1_4
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08200-4
Online ISBN: 978-3-319-08201-1
eBook Packages: Computer ScienceComputer Science (R0)