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Minds and Machines
Erschienen in: Minds and Machines 2/2008

01.06.2008

The Metaphysical Character of the Criticisms Raised Against the Use of Probability for Dealing with Uncertainty in Artificial Intelligence

verfasst von: Carlotta Piscopo, Mauro Birattari

Erschienen in: Minds and Machines | Ausgabe 2/2008

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Abstract

In artificial intelligence (AI), a number of criticisms were raised against the use of probability for dealing with uncertainty. All these criticisms, except what in this article we call the non-adequacy claim, have been eventually confuted. The non-adequacy claim is an exception because, unlike the other criticisms, it is exquisitely philosophical and, possibly for this reason, it was not discussed in the technical literature. A lack of clarity and understanding of this claim had a major impact on AI. Indeed, mostly leaning on this claim, some scientists developed an alternative research direction and, as a result, the AI community split in two schools: a probabilistic and an alternative one. In this article, we argue that the non-adequacy claim has a strongly metaphysical character and, as such, should not be accepted as a conclusive argument against the adequacy of probability.
Vorheriger Artikel Detection of Unfaithfulness and Robust Causal Inference
Nächster Artikel Jenefer Robinson, Deeper than Reason: Emotion and its Role in Literature, Music, and Art

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Fußnoten
1
The chessboard model of the environment has been adopted in several AI applications. In machine learning, for example, different reinforcement learning (Sutton and Barto 1998) techniques such as Q-learning (Watkins 1989) are designed to tackle problems in which the world is represented as a grid and in which objects are represented as points inhabiting the sectors of this grid.
 
2
Just to cite one significant example, the Defense Advanced Research Projects Agency—the agency of the US Department of Defense that is responsible for the development of new technologies for military use—sponsored a robotics research project with the goal of developing an autonomous vehicle running on roads.
 
3
For a broad analysis on the advancements made in the understanding and in the treatment of uncertainty in the last 20 years see (Walley 1991, 1996, 2000).
 
4
This article appears in a collection of works that report the cutting-edge research in fuzzy theory and soft computing. Within this context, the authors draw a demarcation between type one uncertainty and type two uncertainty, meaning by this stochastic uncertainty and deterministic uncertainty, respectively. Then, on the basis of a correspondence-like argumentation, they claim that “fuzzy logic has proven to be a very promising tool for dealing with type two of uncertainty” and they conclude: “Stochastic theory is only effective with type one uncertainty” (Solo and Gupta 2007, p. 257).
 
5
It is worth pointing out here that the issue we have raised above against the demarcation hypothesis is not relevant in this context. Indeed, we are concerned here with a mathematical system: the fact that it is deterministic can be stated on the basis of a formal analysis and does not need to be assessed empirically.
 
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Metadaten
Titel
The Metaphysical Character of the Criticisms Raised Against the Use of Probability for Dealing with Uncertainty in Artificial Intelligence
verfasst von
Carlotta Piscopo
Mauro Birattari
Publikationsdatum
01.06.2008
Verlag
Springer Netherlands
Erschienen in
Minds and Machines / Ausgabe 2/2008
Print ISSN: 0924-6495
Elektronische ISSN: 1572-8641
DOI
https://doi.org/10.1007/s11023-008-9097-3

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