The syntax of choreographies is enhanced with the possibility of writing and invoking recursive procedures, yielding the language of Recursive Choreographies. This opens the door to modelling protocols that allow for retries and data streams of unbounded length. The language of process implementations and the notion of EPP are updated accordingly.

This chapter presents the hypothesis that working memory and language evolved in tandem. It reviews the evolutionary origins of each of the components of Baddeley’s working memory model and their role in the evolution of language. The chapter reviews the gradualist position that language did evolve slowly from aurally directed early primate calls and notes that the primary purpose of language has always been communication. The chapter also presents the novel idea that the pragmatics of speech (the purposes of speech) also evolved in tandem with the evolution of working memory. The chapter also reviews the saltationist idea that something happened to language more recent than 100,000 years ago, and that is the release of the fifth pragmatic of speech, the subjunctive mood, which expresses wishes and ideas contrary to fact. The subjunctive mood required fully modern working memory capacity, sufficient phonological storage capacity, and an enhanced visuospatial sketchpad, which are also critically involved in episodic memory recall and simulation. The phenotypic result of this genotype meant that thought experiments could be conducted in a recursive manner. We propose that the fruits of Homo sapiens’s cultural explosion, cave art, creative figurines, and highly ritualized burials, were the direct result of the wishes and imaginings that arise from subjunctive thinking and subjunctive language.

Chapter 4 focuses in the methodological and instrumental contrasts between artificial economics and mainstream economics. It discusses the mathematical methods of mainstream economics (centered around the use of optimization methods and systems of equations representations) versus the computational methods of artificial economics (characterized by the use of algorithms, software, and computer hardware). Presents basic notions on algorithms, recursion, and Turing machines. And discusses the methodological and instrumental differences between artificial economics and mainstream economics as derived from differences between classical mathematics and constructive mathematics.

This conclusion weaves together the wide-ranging contributions of this volume by considering data-driven personalisation as an internally self-sustaining (autopoietic) system. It observes that like other self-sufficient social systems, personalisation incorporates and processes new data and thereby redefines itself. In doing so it redefines the persons who participate in it, transforming them into ‘digital’ components of this new systems, as well as influencing social arrangements more broadly. The control that elite corporate and governmental entities have over systems of personalisation – which have been diversely described by contributors to this volume – reveals challenges in the taming of personalisation, specifically the limits of traditional means by which free persons address new phenomena – through consent as individuals, and democratic process collectively.

This chapter looks at the cognitive correlates of consciousness, and how consciousness is related to the ideas of selection and limitation. It begins by looking at how cognitive processes such as attention, particularly visual attention, language, thought, mental imagery and inner speech involve consciousness. It looks at cross-cultural differences in cognition. We then look at the neuroscience of the default-mode network. The chapter then looks at a number of models of consciousness based in cognition, including the global workspace theory of Baars, and the multiple drafts model of Dennett. We consider the underlying neuroscience. The chapter then considers how cognition enables us to construct a model or representation of the world, and the way in which consciousness might emerge from that representation. We consider again emergence and complexity. Finally the chapter examines the possible role of quantum mechanics as a basis for understanding consciousness.

This chapter looks at animal consciousness. It begins by asking which animals are conscious, and how we might be able to tell which are and which are not. It moves on to look at the minds of animals, particularly animal intelligence. It then looks at the mirror test of self-recognition, asking whether it is a good guide to detecting consciousness. We consider then which animals feel pain. The chapter moves on to the evolutionary advantages of being conscious, and discusses the importance of possessing a theory of mind for social interaction. It then examines the importance of language and the concept of recursion for consciousness and self-awareness. It concludes by examining panpsychism, the idea that consciousness is a fundamental aspect of all matter.

This chapter surveys what the ethological record reveals about the uniqueness of the human computational system, and explores how linguistic theories account for what ethology may determine to be human-specific. The core computational architecture of the language faculty is compared alongside existing accounts of non-human primates, songbirds and a number of other species, helping to delimit what computational processes electrophysiological models of language need to account for.

This chapter is dedicated to languages of the Americas, with the three main sections covering indigenous languages in North America, Meso-America, and South America. A brief outline of the major language families in the region is given, with the focus on the better-established language families. The last section discusses the issue surrounding Pirahã, a language controversially claimed to lack such basic grammatical mechanisms as recursion.

Perhaps no other part of the ancient world has seen such a lengthy discourse about the fundamental nature of its political organisation, nor seen judgements vary so widely. Practical considerations offer some explanation for the lack of agreement, since both material and textual avenues have suffered from slow and uneven accumulations of reliable data. The difficulty of fieldwork in what are often remote and densely forested regions – where elementary archaeological procedures have long been arduous, time-consuming, and expensive – means that it has taken a good while to fully grasp the physical parameters of the problem. Equally, deciphering the script has proved to be a project of daunting complexity, in which the partial data teased out in one generation have often cast into a different light when a fuller picture emerged in the next. As a result, injections of fresh information, from either domain, have frequently not so much modified existing understandings as sent them careening in new directions.

Chapter 8 analyses and appraises a modern version of an inference about Neanderthal language drawn from data about the experimental making of stone tools by modern humans. This knapping inference looks skeletally as follows, the arrows depicting inferential steps: Modern humans knap Palaeolithic stone tools by means of action sequences structured in terms of hierarchies and recursion → Like modern humans, Neanderthals knapped stone tools by means of action sequences structured in terms of hierarchies and recursion → Like modern humans, Neanderthals processed language by means of action sequences structured in terms of hierarchies and recursion. Probing the submerged components of this inference, Chapter 8 advances two reasons for doubting its soundness. First, the two inferential steps are poorly warranted, involving weak analologies that disregard important differences between Neanderthals and modern humans. Second, the first inferential step lacks appropriate empirical grounding. That is, the sequences involved in the experimental knapping of stone tools by modern humans are not characterised by the hierarchies and recursion used by the syntax of human language.

This chapter explains functions and modules. Functions perform some operation. They can operate directly on data or indirectly via other functions. All the niceties of different kinds of functions are explained. In addition, the topic treats the concept of modules, bits of code that are available to you or other programmers. The chapter shows how you can use existing modules in your own code and how you can write your own modules for others. Finally, the chapter goes into the proper way to document your functions and modules.

This chapter reviews the basic control structures of the Python language. These are used to lay out the logic of a program so as to allow it to do an infinite amount of stuff with finite means. These structures include if, for, while, etc.

This chapter covers the advanced topic of functional programming in Python, introducing the general notion of function programming and then the various tools available in Python to approximate it.