computational theory of mind • substrate neutrality • levels of explanation • episodic and semantic memory • cognitive economy • typicality effect • indicative and deontic reasoning • the gambler’s fallacy • the hot hand fallacy • foraging theory • marginal value theorem

inclusive fitness • direct and indirect fitness • coefficient of relatedness • kin altruism • parental investment • parent–offspring conflict • K- and r-selection • parental manipulation • grandmother hypothesis • non-paternity

reciprocal altruism–direct reciprocation • xenophobia • gift economy • game theory • prisoner’s dilemma • evolutionarily stable strategy • tit-for-tat • stereotyping • ethnocentrism • self-concept • lethal coalitionary aggression • Dark Triad • intimate partner violence

We also found out in Ünlü (2015, p. 264) that Sharwood Smith (1981), Gregg (1984) and Schmidt and Frota (1986) have used the term auto-input to refer to “learners' own output … which learners should make use of to learn a language”.

Without language, social interaction would be impoverished beyond recognition. It enables us to reveal our innermost thoughts to others, or, if the mood takes us, to disguise them with misinformation and lies. With language, action can be coordinated so that a group of people can act as one – even if chimpanzees could conceive of a pyramid they still couldn’t build one because they lack the ability to coordinate action through language. Language also, as we shall see in Chapter 14, enables hard-won knowledge to be passed on to others – including our children – enabling culture to proliferate in ways that would not have been possible in our languageless ancestors (in fact, as we shall see, one theory proposes that language evolve to facilitate cultural transmission). When language evolved it was evolutionary dynamite. Not only did it vastly extend the range of things that ancestral humans were capable of, enabling them, perhaps, to outcompete other hominins around at the time, but it is also likely to have had an impact on the evolution of the brain itself. It is unlikely that our languageless ancestors had brains identical to ours but lacking the appropriate language circuitry; it is more likely that the gradual evolution of communicative sophistication led to huge leaps in the way that we interact with others. So great are the advantages of language to our species that surely it must have been the product of natural (or sexual) selection.

Welcome to the world of statistical programming. We will start in this chapter by giving you an idea of what statistical programming is all about. We will also tell you what to expect as you proceed through the rest of the book. The chapter will finish with some instructions about how to download and install R, the software package and language on which we base our programming examples, and RStudio, an “integrated development environment” (or “IDE”) for R.

The word “input” is used in our everyday conversation to mean something that we put into a system, organisation or device. For example, input can be energy that can be put into an energy-supply circuit, resources that are put into a company or information that is fed to a computer.

Linear algebra deals with vector spaces and linear operations on them. In mathematics, we usually represent vectors as column vectors of numbers, and linear operations as matrices. Applying a linear operation to a vector becomes multiplication of a column vector by a matrix, and composition of operations is matrix multiplication.

natural selection • heritable variation • reproductive success • fitness • genes • chromosomes • Mendelian genetics • genotype • phenotype • mutation • DNA • heritability of characteristics • genome-wide association • behavioural epigenetics • group selection • individual selection • gene selection • altruism • the selfish gene

In statistical modeling, we may want to find a set of parameters for a model which minimize the expected prediction errors for the model.

personality • niche fitting • heritability • frequency-dependent selection • genome-wide association studies (GWAS) • intelligence • general intelligence (g) • multiple intelligences • Savanna-IQ Interaction Hypothesis • single nucleotide polymorphisms

So far, in Chapter 1 we have defined input as multimodal data that the receiver is exposed to during communication. We have identified the kinds and nature of input, and have discussed contemporary and interdisciplinary issues that have tended to be overlooked in past studies.