By Bas Steunebrink, Pei Wang, Ben Goertzel
This booklet constitutes the refereed complaints of the ninth foreign convention on synthetic basic 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 rigorously reviewed and chosen from sixty seven submissions. AGI study differs from the normal AI examine by way of stressing at the versatility and wholeness of intelligence, and by way of undertaking the engineering perform in accordance with an summary of a method such as the human brain inSelf a undeniable sense.
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Additional info for Artificial General Intelligence: 9th International Conference, AGI 2016, New York, NY, USA, July 16-19, 2016, Proceedings
4 Known Environments: AIμ In this section we show that a universal agent’s behaviour can depend on the reward range. This is a surprising result, because in a standard RL setup in 4 5 To compare an agent’s behaviour in μ with that in μ , we should also augment its policy π so that it is deﬁned over (A × Ed )∗ . Since actions taken once in the death-state are inconsequential, however, this modiﬁcation is purely technical and for simplicity we still refer to the augmented policy as π. If the two formalisations predicted diﬀerent behaviour, or were only applicable in incomparable environment classes, we might worry that our results were more reﬂective of our model choice than of any general property of intelligent agents.
In: UAI-15, pp. 464–473. AUAI Press (2015). 05572 5. : An Introduction to Kolmogorov Complexity and its Applications, 3rd edn. Springer, Heidelberg (2008) 6. : Death and suicide in universal artiﬁcial intelligence. Technical report ANU (2016). 00652 7. : The basic AI drives. In: AGI-08, pp. 483–493. IOS Press (2008) 8. : Corrigibility. In: AAAI Workshop on AI and Ethics, pp. 74–82 (2015) 9. : Complexity-based induction systems: comparisons and convergence theorems. IEEE Trans. Inf. Theor. IT–24, 422–432 (1978) 10.
Firstly, it illustrates that a death-reward rd = 0 implicitly attends semimeasure-death. That is, an agent that models the environment using semimeasures behaves as if the deathreward is zero, even though that value is nowhere explicitly represented. 5 In the remainder of this paper we deploy these formal models to analyse the behaviour of universal agents, which are themselves models of general intelligence. We hope that this will serve as a preliminary sketch of the general behavioural characteristics of value-maximising agents in relation to death.
Artificial General Intelligence: 9th International Conference, AGI 2016, New York, NY, USA, July 16-19, 2016, Proceedings by Bas Steunebrink, Pei Wang, Ben Goertzel