In 2018 we marked the 250th anniversary of the founding of the modern circus, an event traced to the entrepreneurial initiatives of Philip Astley (1742–1814). Astley enclosed a circle of ground on the south side of the Thames in 1768 where he exhibited his unusual equestrian skills for a paying public. The circus’s specialised history in different parts of the globe reveals that for just over 250 years this hybrid entertainment, with its own codes of physical and comic performance, visuality, and business management, has developed and diversified through multiple cycles of reinvention. Oscillating through phases of illegitimacy on the fringes of society and validation for its aesthetic and entertainment appeal, the circus’s restless evolution has always been influenced by unique confluences of the political environment, artistic heritage, and aesthetic trends particular to its geographic context.

There is a long history of software programs that implement creativity, imagery, and imagination. They are used for generation of entertainment, creation of art, and simulation of the world. Some of these programs are created to shed light on the nature of imagination, and some are explicitly designed to model imagination in humans. These AIs also display a range of domain areas, from the creation of paintings, music, and plot structures, to the generation of entire fictional worlds. AI aids our understanding of imagination in several ways: It provides ideas of how it could work, it tests the feasibility of theories, and brings to light assumptions and new problems that are difficult to generate from theories that are only described in words.

Artificial intelligence (AI) is a scientific discipline that seeks to understand intelligence through the design and construction of intelligent machines. AI and cognitive science have a strong two-way relationship: Cognitive psychology often has inspired AI theories, and AI research has led to new theories of cognition that have been tested through psychological experimentation. While AI theories of cognition often are under-constrained, cognitive theories of AI tend to be over-constrained. Nevertheless, AI is useful for cognitive psychologists both as a source of new ideas and insights, and an experimental testbed. In this chapter, we describe some of the basic concepts and methods of AI by taking robot navigation in a city as an illustrative example. We also briefly discuss the history of AI, methods for assessing progress in AI, and some of AI’s potential impacts on society.

In a study of some of the more prosperous middle-class Irish migrants to London in the eighteenth century, Craig Bailey has argued that it is important to emphasise ‘the possibilities rather than the limits of Irishness’ and that ‘Irish identity was far too important for most middle-class Irish to jettison’.1 The largest population of middle-class Irishmen outside of Ireland was resident in London in the eighteenth century, but, says Bailey, ‘scholars have mistaken the identity of middle-class migrants by making poverty the touchstone of Irishness, and by presuming that visible Irish characteristics such as language, accent and name necessarily had negative meanings’.2