Download Artificial General Intelligence: 9th International by Bas Steunebrink, Pei Wang, Ben Goertzel PDF

By Bas Steunebrink, Pei Wang, Ben Goertzel

This ebook constitutes the refereed complaints of the ninth overseas convention on synthetic normal Intelligence, AGI 2016, held in long island urban, manhattan, united states, in July 2016 as a part of HLAI 2016, the Joint Multi-Conference on Human-Level synthetic Intelligence 2016.

The 24 complete papers, 2 brief papers, and 10 poster papers awarded have been conscientiously reviewed and chosen from sixty seven submissions. AGI learn differs from the normal AI learn by means of stressing at the versatility and wholeness of intelligence, and through engaging in the engineering perform in keeping with an summary of a process such as the human brain inSelf a definite sense.

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Extra info for Artificial General Intelligence: 9th International Conference, AGI 2016, New York, NY, USA, July 16-19, 2016, Proceedings

Sample text

By interpreting r more generally as a value-evidence signal, the VRL framework also covers other forms of value learning. For example, IRL fits into the VRL framework by letting R be a set of principal actions, and letting C(r | s, u) be the probability that a principal with utility function u takes action r in the state s. Open Questions. While promising, the results established in this paper only provide a tentative starting point for solving the wireheading problem. Everitt and Hutter (2016) lists many directions of future work.

The CP-VRL agent thus avoids wireheading in the same sense as the utility agent of Definition 8. 6 In this analogy, a self-deluding action would be to decide to look inside a fridge while at the same time putting a picture of milk in front of my eyes. 20 T. Everitt and M. Hutter Justifying the Replacement of ˇr with r. We are now in position to justify the replacement of rˇ with r in C(u | s, r). All we have shown so far is that an agent using C(u | s, r) ∝ C(u)C(r | s, u) will avoid wireheading.

Everitt and Hutter (2016) lists many directions of future work. An important next step is a generalisation from the one-shot scenario in this paper, where the agent takes one action and receives one reward. Potentially, a much richer set of questions can be asked in sequential settings. Acknowledgements. We thank Jan Leike and Jarryd Martin for proof reading and giving valuable suggestions. 7 Technically, it is possible that the agent self-deludes by a CP action. However, the agent has no incentive to do so, and inadvertent self-delusion is typically implausible.

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