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Reward Function Integrity in Artificially Intelligent Systems

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    abhishek
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    Video and abstract of Roman’s presentation at Oxford University. Analysis of historical examples of wireheading in man and machine and evaluate a number of approaches proposed for dealing with reward-function corruption. While simplistic optimizers driven to maximize a proxy measure for a particular goal will always be a subject to corruption, sufficiently rational self-improving machines are believed by many to be safe from wireheading problems.

    [See the full post at: Reward Function Integrity in Artificially Intelligent Systems]

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