scholarly journals Experimental evolutionary simulations of learning, memory and life history

2020 ◽  
Vol 375 (1803) ◽  
pp. 20190504 ◽  
Author(s):  
Thomas J. H. Morgan ◽  
Jordan W. Suchow ◽  
Thomas L. Griffiths
Keyword(s):  
Life History ◽  
Human Mind ◽  
Human Behaviour ◽  
Theme Issue ◽  
Evolutionary Simulation ◽  
Cognition And Culture ◽  
Human Participants ◽  
Evolutionary Simulations ◽  
Rapid Environmental Change ◽  
Theory And Experiment

Humans possess an unusual combination of traits, including our cognition, life history, demographics and geographical distribution. Many theories propose that these traits have coevolved. Such hypotheses have been explored both theoretically and empirically, with experiments examining whether human behaviour meets theoretical expectations. However, theory must make assumptions about the human mind, creating a potentially problematic gap between models and reality. Here, we employ a series of ‘experimental evolutionary simulations' to reduce this gap and to explore the coevolution of learning, memory and childhood. The approach combines aspects of theory and experiment by inserting human participants as agents within an evolutionary simulation. Across experiments, we find that human behaviour supports the coevolution of learning, memory and childhood, but that this is dampened by rapid environmental change. We conclude by discussing both the implications of these findings for theories of human evolution and the utility of experimental evolutionary simulations more generally. This article is part of the theme issue ‘Life history and learning: how childhood, caregiving and old age shape cognition and culture in humans and other animals'.

scholarly journals Childhood as a solution to explore–exploit tensions

2020 ◽  
Vol 375 (1803) ◽  
pp. 20190502 ◽  
Author(s):  
Alison Gopnik
Keyword(s):  
Life History ◽  
Empirical Evidence ◽  
Old Age ◽  
Early Period ◽  
Cognitive Profile ◽  
External Information ◽  
Theme Issue ◽  
Older Learners ◽  
Trade Offs ◽  
Cognition And Culture

I argue that the evolution of our life history, with its distinctively long, protected human childhood, allows an early period of broad hypothesis search and exploration, before the demands of goal-directed exploitation set in. This cognitive profile is also found in other animals and is associated with early behaviours such as neophilia and play. I relate this developmental pattern to computational ideas about explore–exploit trade-offs, search and sampling, and to neuroscience findings. I also present several lines of empirical evidence suggesting that young human learners are highly exploratory, both in terms of their search for external information and their search through hypothesis spaces. In fact, they are sometimes more exploratory than older learners and adults. This article is part of the theme issue ‘Life history and learning: how childhood, caregiving and old age shape cognition and culture in humans and other animals’.

scholarly journals Cognitive consequences of our grandmothering life history: cultural learning begins in infancy

2020 ◽  
Vol 375 (1803) ◽  
pp. 20190501 ◽  
Author(s):  
Kristen Hawkes
Keyword(s):  
Life History ◽  
Old Age ◽  
Social Relationships ◽  
Brain Size ◽  
Great Apes ◽  
Cultural Learning ◽  
Theme Issue ◽  
Economic Productivity ◽  
Shared Intentionality ◽  
Cognition And Culture

Postmenopausal longevity distinguishes humans from our closest living evolutionary cousins, the great apes, and may have evolved in our lineage when the economic productivity of grandmothers allowed mothers to wean earlier and overlap dependents. Since increased longevity retards development and expands brain size across the mammals, this hypothesis links our slower developing, bigger brains to ancestral grandmothering. If foraging interdependence favoured postmenopausal longevity because grandmothers' subsidies reduced weaning ages, then ancestral infants lost full maternal engagement while their slower developing brains were notably immature. With survival dependent on social relationships, sensitivity to reputations is wired very early in neural ontogeny, beginning our lifelong preoccupation with shared intentionality. This article is part of the theme issue ‘Life history and learning: how childhood, caregiving and old age shape cognition and culture in humans and other animals’.

scholarly journals The elaboration of exploratory play

2020 ◽  
Vol 375 (1803) ◽  
pp. 20190503 ◽  
Author(s):  
Maddie Pelz ◽  
Celeste Kidd
Keyword(s):  
Life History ◽  
Quantitative Method ◽  
Human Life ◽  
Theme Issue ◽  
Exploratory Play ◽  
Cast Doubt ◽  
The Usa ◽  
Cognition And Culture ◽  
Age Range ◽  
Insight Into

We apply a new quantitative method for investigating how children's exploration changes across age in order to gain insight into how exploration unfolds over the course of a human life from a life-history perspective. In this study, different facets of exploratory play were quantified using a novel touchscreen environment across a large sample and wide age range of children in the USA ( n = 105, ages = 1 year and 10 months to 12 years and 2 months). In contrast with previous theories that have suggested humans transition from more exploratory to less throughout maturation, we see children transition from less broadly exploratory as toddlers to more efficient and broad as adolescents. Our data cast doubt on the picture of human life history as involving a linear transition from more curious in early childhood to less curious with age. Instead, exploration appears to become more elaborate throughout human childhood. This article is part of the theme issue ‘Life history and learning: how childhood, caregiving and old age shape cognition and culture in humans and other animals’.

scholarly journals The emergence of emotionally modern humans: implications for language and learning

2020 ◽  
Vol 375 (1803) ◽  
pp. 20190499 ◽  
Author(s):  
Sarah Blaffer Hrdy ◽  
Judith M. Burkart
Keyword(s):  
Life History ◽  
Old Age ◽  
Cooperative Breeding ◽  
Mental States ◽  
Social Contexts ◽  
Social Selection ◽  
Theme Issue ◽  
Modern Humans ◽  
Male And Female ◽  
Cognition And Culture

According to the Cooperative Breeding Hypothesis, apes with the life-history attributes of those in the line leading to the genus Homo could not have evolved unless male and female allomothers had begun to help mothers care for and provision offspring. As proposed elsewhere, the unusual way hominins reared their young generated novel phenotypes subsequently subjected to Darwinian social selection favouring those young apes best at monitoring the intentions, mental states and preferences of others and most motivated to attract and appeal to caretakers. Not only were youngsters acquiring information in social contexts different from those of other apes, but they would also have been emotionally and neurophysiologically different from them in ways that are relevant to how humans learn. Contingently delivered rewards to dependents who attracted and ingratiated themselves with allomothers shaped their behaviours and vocalizations and transformed the way developing youngsters learned from others and internalized their preferences. This article is part of the theme issue ‘Life history and learning: how childhood, caregiving and old age shape cognition and culture in humans and other animals’.

scholarly journals The Nature of Decision-Making: Human Behavior vs. Machine Learning

2019 ◽  
Vol 2 (2) ◽  
pp. 9-10
Author(s):  
Keeya Beausoleil ◽  
Craig Chapman ◽  
Taher Jafferjee ◽  
Nathan Wispinski ◽  
Scott Stone
Keyword(s):  
Human Mind ◽  
Human Behaviour ◽  
Artificial Agents ◽  
Strategic Games ◽  
Artificial Agent ◽  
Adequate Model ◽  
Overall Performance ◽  
Human Participants ◽  
Greedy Policy

Artificial agents have often been compared to humans in their ability to categorize images or play strategic games. However, comparisons between human and artificial agents are frequently based on the overall performance on a particular task, and not necessarily on the specifics of how each agent behaves. In this study, we directly compared human behaviour with a reinforcement learning (RL) model. Human participants and an RL agent navigated through different grid world environments with high- and low- value targets. The artificial agent consisted of a deep neural network trained to map pixel input of a 27x27 grid world into cardinal directions using RL. An epsilon greedy policy was used to maximize reward. Behaviour of both agents was evaluated on four different conditions. Results showed both humans and RL agents consistently chose the higher reward over a lower reward, demonstrating an understanding of the task. Though both humans and RL agents consider movement cost for reward, the machine agent considers the movement costs more, trading off the effort with reward differently than humans. We found humans and RL agents both consider long-term rewards as they navigate through the world, yet unlike humans, the RL model completely disregards limitations in movements (e.g. how many total moves received). Finally, we rotated pseudorandom grid arrangements to study how decisions change with visual differences. We unexpectedly found that the RL agent changed its behaviour due to visual rotations, yet remained less variable than humans. Overall, the similarities between humans and the RL agent shows the potential RL agents have of being an adequate model of human behaviour. Additionally, the differences between human and RL agents suggest improvements to RL methods that may improve their performance. This research compares the human mind with artificial intelligence, creating the opportunity for future innovation.

scholarly journals Autistic Spectrum Disorder in Prehistory

2011 ◽  
Vol 21 (3) ◽  
pp. 357-364 ◽  
Author(s):  
Catriona Pickard ◽  
Ben Pickard ◽  
Clive Bonsall
Keyword(s):  
Population Level ◽  
Human Mind ◽  
Modern Human ◽  
Human Behaviour ◽  
Specific Reference ◽  
Autistic Spectrum ◽  
Evolutionary Advantage ◽  
New Ideas ◽  
Spectrum Disorders ◽  
Neuropsychiatric Conditions

Individuals with ‘extraordinary’ or ‘different’ minds have been suggested to be central to invention and the spread of new ideas in prehistory, shaping modern human behaviour and conferring an evolutionary advantage at population level. In this article the potential for neuropsychiatric conditions such as autistic spectrum disorders to provide this difference is explored, and the ability of the archaeological record to provide evidence of human behaviour is discussed. Specific reference is made to recent advances in the genetics of these conditions, which suggest that neuropsychiatric disorders represent a non-advantageous, pathological extreme of the human mind and are likely a by-product rather than a cause of human cognitive evolution.

scholarly journals The importance of life history and population regulation for the evolution of social learning

2020 ◽  
Vol 375 (1803) ◽  
pp. 20190492 ◽  
Author(s):  
Dominik Deffner ◽  
Richard McElreath
Keyword(s):  
Life History ◽  
Social Learning ◽  
Age Structure ◽  
Life Histories ◽  
Population Regulation ◽  
Individual Learning ◽  
Vital Rates ◽  
Strategic Learning ◽  
Cognition And Culture ◽  
Exemplary Model

Social learning and life history interact in human adaptation, but nearly all models of the evolution of social learning omit age structure and population regulation. Further progress is hindered by a poor appreciation of how life history affects selection on learning. We discuss why life history and age structure are important for social learning and present an exemplary model of the evolution of social learning in which demographic properties of the population arise endogenously from assumptions about per capita vital rates and different forms of population regulation. We find that, counterintuitively, a stronger reliance on social learning is favoured in organisms characterized by ‘fast’ life histories with high mortality and fertility rates compared to ‘slower’ life histories typical of primates. Long lifespans make early investment in learning more profitable and increase the probability that the environment switches within generations. Both effects favour more individual learning. Additionally, under fertility regulation (as opposed to mortality regulation), more juveniles are born shortly after switches in the environment when many adults are not adapted, creating selection for more individual learning. To explain the empirical association between social learning and long life spans and to appreciate the implications for human evolution, we need further modelling frameworks allowing strategic learning and cumulative culture. This article is part of the theme issue ‘Life history and learning: how childhood, caregiving and old age shape cognition and culture in humans and other animals’.

scholarly journals Innovation, life history and social networks in human evolution

2020 ◽  
Vol 375 (1803) ◽  
pp. 20190497 ◽  
Author(s):  
Kim Sterelny
Keyword(s):  
Life History ◽  
General Pattern ◽  
Network Characteristics ◽  
Social Lives ◽  
Hominin Evolution ◽  
Community Boundaries ◽  
Female Dispersal ◽  
Technological Tradition ◽  
Early Hominin ◽  
Cognition And Culture

There is a famous puzzle about the first 3 million years of archaeologically visible human technological history. The pace of change, of innovation and its uptake, is extraordinarily slow. In particular, the famous handaxes of the Acheulian technological tradition first appeared about 1.7 Ma, and persisted with little change until about 800 ka, perhaps even longer. In this paper, I will offer an explanation of that stasis based in the life history and network characteristics that we infer (on phylogenetic grounds) to have characterized earlier human species. The core ideas are that (i) especially in earlier periods of hominin evolution, we are likely to find archaeological traces only of widespread and persisting technologies and practices; (ii) the record is not a record of the rate of innovation, but the rate of innovations establishing in a landscape; (iii) innovations are extremely vulnerable to stochastic loss while confined to the communities in which they are made and established; (iv) the export of innovation from the local group is sharply constrained if there is a general pattern of hostility and suspicion between groups, or even if there is just little contact between adults of adjoining groups. That pattern is typical of great apes and likely, therefore, to have characterized at least early hominin social lives. Innovations are unlikely to spread by adult-to-adult interactions across community boundaries. (v) Chimpanzees and bonobos are characterized by male philopatry and subadult female dispersal; that is, therefore, the most likely early hominin pattern. If so, the only innovations at all likely to expand beyond the point of origin are those acquired by subadult females, and ones that can be expressed by those females, at high enough frequency and salience for them to spread, in the bands that the females join. These are very serious filters on the spread of innovation. This article is part of the theme issue ‘Life history and learning: how childhood, caregiving and old age shape cognition and culture in humans and other animals’.

scholarly journals Live human–robot interactive public demonstrations with automatic emotion and personality prediction

2019 ◽  
Vol 374 (1771) ◽  
pp. 20180026 ◽  
Author(s):  
Hatice Gunes ◽  
Oya Celiktutan ◽  
Evangelos Sariyanidi
Keyword(s):  
Facial Expressions ◽  
Humanoid Robot ◽  
Lessons Learned ◽  
Human Robot Interaction ◽  
Theme Issue ◽  
Science And Engineering ◽  
Robot Interaction ◽  
Personality Prediction ◽  
Human Participants ◽  
Public Demonstrations

Communication with humans is a multi-faceted phenomenon where the emotions, personality and non-verbal behaviours, as well as the verbal behaviours, play a significant role, and human–robot interaction (HRI) technologies should respect this complexity to achieve efficient and seamless communication. In this paper, we describe the design and execution of five public demonstrations made with two HRI systems that aimed at automatically sensing and analysing human participants’ non-verbal behaviour and predicting their facial action units, facial expressions and personality in real time while they interacted with a small humanoid robot. We describe an overview of the challenges faced together with the lessons learned from those demonstrations in order to better inform the science and engineering fields to design and build better robots with more purposeful interaction capabilities. This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.

scholarly journals Introduction to special issue: ‘Life history and learning: how childhood, caregiving and old age shape cognition and culture in humans and other animals’

2020 ◽  
Vol 375 (1803) ◽  
pp. 20190489
Author(s):  
Alison Gopnik ◽  
Willem E. Frankenhuis ◽  
Michael Tomasello
Keyword(s):  
Life History ◽  
Old Age ◽  
Developmental Psychology ◽  
Human Life ◽  
Empirical Work ◽  
Reproductive Rate ◽  
Special Issue ◽  
Wide Range ◽  
Cognition And Culture ◽  
High Level

This special issue focuses on the relationship between life history and learning, especially during human evolution. ‘Life history’ refers to the developmental programme of an organism, including its period of immaturity, reproductive rate and timing, caregiving investment and longevity. Across many species an extended childhood and high caregiving investment appear to be correlated with particular kinds of plasticity and learning. Human life history is particularly distinctive; humans evolved an exceptionally long childhood and old age, and an unusually high level of caregiving investment, at the same time that they evolved distinctive capacities for cognition and culture. The contributors explore the relations between life history, plasticity and learning across a wide range of methods and populations, including theoretical and empirical work in biology, anthropology and developmental psychology. This article is part of the theme issue ‘Life history and learning: how childhood, caregiving and old age shape cognition and culture in humans and other animals’.

Sign in / Sign up

Export Citation Format

Share Document