Bootstrapping trust and stereotypes with tags

In real-world environments, cooperation often emerges amongst agents who are observably similar. Estimating the expected behaviour of another agent is a challenging problem, particularly for new agents who have little or no experience of others. In this paper, we show how observable features can be used to find similar, and hence cooperative, partners. Our contribution extends trust and stereotype approaches, to include comparisons and learning of observable features, called tags. In environments where no reciprocity exists (or where there have been insuf- ficient interactions for reciprocity to take effect) tags have been used to encourage cooperation. The only information available to an agent early in its life is knowledge of its own tags and behaviour. We assume that agents who are observably similar will be behaviourally similar too. Agents use reinforcement learning to take advantage of as much available information as possible, until sufficient experience has been gathered for more established trust and stereotype models to be built. Our results show that using tags improves agents’ rewards in the early stages of their lifetime when used prior to established stereotype and trust algorithms. We demonstrate that tags are successful in supporting cooperation, even when agent behaviour is independent of the partner, because the approach correctly identifies similar agents. Good agents are able to select partners who will act as they do, while bad agents avoid those who are observably similar

The Global Risks Report 2016, 11th Edition

Now in its 11th edition, The Global Risks Report 2016 draws attention to ways that global risks could evolve and interact in the next decade. The year 2016 marks a forceful departure from past findings, as the risks about which the Report has been warning over the past decade are starting to manifest themselves in new, sometimes unexpected ways and harm people, institutions and economies. Warming climate is likely to raise this year's temperature to 1° Celsius above the pre-industrial era, 60 million people, equivalent to the world's 24th largest country and largest number in recent history, are forcibly displaced, and crimes in cyberspace cost the global economy an estimated US$445 billion, higher than many economies' national incomes. In this context, the Reportcalls for action to build resilience – the "resilience imperative" – and identifies practical examples of how it could be done.The Report also steps back and explores how emerging global risks and major trends, such as climate change, the rise of cyber dependence and income and wealth disparity are impacting already-strained societies by highlighting three clusters of risks as Risks in Focus. As resilience building is helped by the ability to analyse global risks from the perspective of specific stakeholders, the Report also analyses the significance of global risks to the business community at a regional and country-level

From single neurons to social brains

The manufacture of stone tools is an integral part of the human evolutionary trajectory. However, very little research is directed towards the social and cognitive context of the process of manufacture. This article aims to redress this balance by using insights from contemporary neuroscience. Addressing successively more inclusive levels of analysis, we will argue that the relevant unit of analysis when examining the interface between archaeology and neuroscience is not the individual neuron, nor even necessarily the individual brain, but instead the socio-cognitive context in which brains develop and tools are manufactured and used. This context is inextricably linked to the development of unique ontogenetic scheduling, as evidenced by the fossil record of evolving hominin lineages

Evolutionary dynamics in structured populations

Evolutionary dynamics shape the living world around us. At the centre of every evolutionary process is a population of reproducing individuals. The structure of that population affects evolutionary dynamics. The individuals can be molecules, cells, viruses, multicellular organisms or humans. Whenever the fitness of individuals depends on the relative abundance of phenotypes in the population, we are in the realm of evolutionary game theory. Evolutionary game theory is a general approach that can describe the competition of species in an ecosystem, the interaction between hosts and parasites, between viruses and cells, and also the spread of ideas and behaviours in the human population. In this perspective, we review the recent advances in evolutionary game dynamics with a particular emphasis on stochastic approaches in finite sized and structured populations. We give simple, fundamental laws that determine how natural selection chooses between competing strategies. We study the well-mixed population, evolutionary graph theory, games in phenotype space and evolutionary set theory. We apply these results to the evolution of cooperation. The mechanism that leads to the evolution of cooperation in these settings could be called ‘spatial selection’: cooperators prevail against defectors by clustering in physical or other spaces

Indirect reciprocity and the evolution of prejudicial groups

Prejudicial attitudes are widely seen between human groups, with significant consequences. Actions taken in light of prejudice result in discrimination, and can contribute to societal division and hostile behaviours. We define a new class of group, the prejudicial group, with membership based on a common prejudicial attitude towards the out-group. It is assumed that prejudice acts as a phenotypic tag, enabling groups to form and identify themselves on this basis. Using computational simulation, we study the evolution of prejudicial groups, where members interact through indirect reciprocity. We observe how cooperation and prejudice coevolve, with cooperation being directed in-group. We also consider the co-evolution of these variables when out-group interaction and global learning are immutable, emulating the possible pluralism of a society. Diversity through three factors is found to be influential, namely out-group interaction, out-group learning and number of sub-populations. Additionally populations with greater in-group interaction promote both cooperation and prejudice, while global rather than local learning promotes cooperation and reduces prejudice. The results also demonstrate that prejudice is not dependent on sophisticated human cognition and is easily manifested in simple agents with limited intelligence, having potential implications for future autonomous systems and human-machine interaction

Exploring social gambling: scoping, classification and evidence review

The aim of this report is to speculate on the level of concern we might have regarding consumer risk in relation to ‘social gambling.’ In doing so, this report is intended to help form the basis to initiate debate around a new and under-researched social issue; assist in setting a scientific research agenda; and, where appropriate, highlight concerns about any potential areas that need to be considered in terms of precautionary regulation. This report does not present a set of empirical research findings regarding ‘social gambling’ but rather gathers information to improve stakeholder understanding