Abstract
This chapter is a summary of my talk given during the 19th International Multiconference on Advanced Computer Systems held in Miedzyzdroje, Poland in October 2014. The talk started with the Legg and Hutter’s formal definition of what they call Universal Machine Intelligence which aims to measure intelligence of almighty robot, where agents are given an infinitely large number of different types of task to measure its universal intelligence. We take it a consideration what if we apply the formula to only one specific task. We claim the measurement of performance for each of those tasks given in the Legg and Hutter’s definition is not sufficient to represent agent’s intelligence. Then, we present our ongoing definition of machine intelligence for a specific one task such as forecasting stock market price.
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Acknowledgments
The author greatly thanks Professor Jerzy Pejaś and the other organizing committee members of this conference for constantly inviting me to a series of this conference with wonderful atmosphere in a beautiful small town in Poland along the Baltic Sea. To take part in this conference has always been giving me a big motivation to proceed my reflection to what is machine intelligence.
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Imada, A. (2015). What Is Machine Intelligence? A Case Study: Stock Market Forecasting Agents. In: Wiliński, A., Fray, I., Pejaś, J. (eds) Soft Computing in Computer and Information Science. Advances in Intelligent Systems and Computing, vol 342. Springer, Cham. https://doi.org/10.1007/978-3-319-15147-2_1
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