(Enter summary)
Abstract: Decision theory formally solves the problem of
rational agents in uncertain worlds if the true
environmental probability distribution is known. (Update)
Context of citations to this paper: More
...been introduced and discussed in March 2000 in [Hut00] in a 62 page long report. More succinct descriptions have been published in [Hut01d, Hut01e]. The AI# model has been argued to formally solve a number of problem classes, including sequence prediction, strategic games,...
...an environment can also use predictions of the future to compute action sequences that maximize expected future reward. Hutter s AIXI model [10] does exactly this, by combining Solomonoff s M based universal prediction scheme with an expectimax computation. It can be shown...
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BibTeX entry: (Update)
M. Hutter. Towards a universal theory of artificial intelligence based on algorithmic probability and sequential decisions. Proceedings of the 12 Eurpean Conference on Machine Learning (ECML-2001), pages 226--238, 2001. http://citeseer.ist.psu.edu/hutter00towards.html More
@article{ hutter01towards,
author = "Marcus Hutter",
title = "Towards a Universal Theory of Artificial Intelligence Based on Algorithmic Probability and Sequential Decisions",
journal = "Lecture Notes in Computer Science",
volume = "2167",
pages = "226--??",
year = "2001",
url = "citeseer.ist.psu.edu/hutter00towards.html" }
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