The Multi-slot Framework: A Formal Model for Multiple, Copiable AIs

Orseau, Laurent

doi:10.1007/978-3-319-09274-4_10

Cited by 3 publications

(1 citation statement)

References 13 publications

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“…[16,26,68] • How should agents reason about other agents reasoning about themselves? [47] • Personal identity and teleportation [62,63].…”

Section: Fundamental Challengesmentioning

confidence: 99%

Universal Artificial Intelligence

Hutter

2018

Foundations of Trusted Autonomy

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Artificial intelligence (AI) bears the promise of making us all healthier, wealthier, and happier by reducing the need for human labour and by vastly increasing our scientific and technological progress.Since the inception of the AI research field in the mid-twentieth century, a range of practical and theoretical approaches have been investigated. This chapter will discuss universal artificial intelligence (UAI) as a unifying framework and foundational theory for many (most?) of these approaches. The development of a foundational theory has been pivotal for many other research fields. Well-known examples include the development of Zermelo-Fraenkel set theory (ZFC) for mathematics, Turingmachines for computer science, evolution for biology, and decision and game theory for economics and the social sciences. Successful foundational theories give a precise, coherent understanding of the field, and offer a common language for communicating research. As most research studies focus on one narrow question, it is essential that the value of each isolated result can be appreciated in light of a broader framework or goal formulation. UAI offers several benefits to AI research beyond the general advantages of foundational theories just mentioned. Substantial attention has recently been called to the safety of autonomous AI systems [10]. A highly intelligent autonomous system may cause substantial unintended harm if constructed carelessly. The trustworthiness of autonomous agents may be much improved if their design is grounded in a formal theory (such as UAI) that allows formal verification of their behavioural properties. Unsafe designs can be ruled out at an early stage, and adequate attention can be given to crucial design choices.

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“…[16,26,68] • How should agents reason about other agents reasoning about themselves? [47] • Personal identity and teleportation [62,63].…”

Section: Fundamental Challengesmentioning

confidence: 99%