The development of Artificial General Intelligence (AGI) promises to be a major event. Along
with its many potential benefits, it also raises serious safety concerns (Bostrom, 2014). The …

In this chapter we review the evidence for and against three claims: that (1) there is a
substantial chance we will create human-level AI before 2100, that (2) if human-level AI is …

Active learning connects students to the real life situations they will encounter in their future
jobs. In hospitality education, active learning implements various lively, fun activities to …

Reinforcement Learning (RL) algorithms typically utilize learning and/or planning
techniques to derive effective policies. The integration of both approaches has proven to be …

The field of artificial intelligence has recently experienced a number of breakthroughs thanks
to progress in deep learning and reinforcement learning. Computer algorithms now …

A big open question of algorithmic information theory is the choice of the universal Turing
machine (UTM). For Kolmogorov complexity and Solomonoff induction we have invariance …

We define an optimal Bayesian knowledge-seeking agent, KL-KSA, designed for countable
hypothesis classes of stochastic environments and whose goal is to gather as much …

Foundational theories have contributed greatly to scientific progress in many fields.
Examples include Zermelo-Fraenkel set theory in mathematics, and universal Turing …

Any agent that is part of the environment it interacts with and has versatile actuators (such as
arms and fingers), will in principle have the ability to self-modify–for example by changing its …

Computational creativity (CC) seeks to endow artificial systems with creativity. Although
human creativity is known to be substantially driven by intrinsic motivation (IM), most CC …