Eric Silverman

Linked lives: the utility of an agent-based approach to modeling partnership and household formation in the context of social care

The UKs population is aging, which presents a challenge as older people are the primary users of health and social care services. We present an agent-based model of the basic demographic processes that impinge on the supply of, and demand for, social care: namely mortality, fertility, health-status transitions, internal migration, and the formation and dissolution of partnerships and households. Agent-based modeling is used to capture the idea of “linked lives” and thus to represent hypotheses that are impossible to express in alternative formalisms. Simulation runs suggest that the per-taxpayer cost of state-funded social care could double over the next forty years. A key benefit of the approach is that we can treat the average cost of state-funded care as an outcome variable, and examine the projected effect of different sets of assumptions about the relevant social processes.

From artificial societies to new social science theory

We identify two distinct themes in social science modelling. One, more specific, approach is that of social simulation which addresses how behaviour of many actors can lead to emergent effects. We argue that this approach, while useful as a tool in social science policy development, is fundamentally constrained due to the fact that its models are developed within the society they are supposed to model. Alternatively, the second theme looks to take a more holistic view by taking inspiration from systems sociology. This approach looks to build societies from the bottom up and may allow us to generate new perspectives in social theory.

Complex systems modeling for supply and demand in health and social care

This paper introduces a major new cross-disciplinary research project that looks at the UK health and social care system, as part of an ambitious, broader initiative to apply methods from complexity science to a range of key global challenges. This particular project aims to develop new, integrated models for the supply and demand of both health and social care, in the context of the societal change brought about by migration, mobility and the ageing population. We discuss the background to the work, and the broad way in which we intend to leverage complexity science. This is made more specific with a brief discussion on existing demographic models, and some examples of model-building in progress. We conclude with a glimpse into the subtly difficult problems of fostering such innovative interdisciplinarity.

Model-Based Demography: Towards a Research Agenda

This chapter aims to contribute to the debate on the role of model-based approaches, such as agent-based modelling, in the future of demography. First we call attention to the developments of the discipline since the seventeenth century, and we describe its four successive paradigms related to the period, cohort, event-history and multilevel perspectives. We argue that these paradigms are complementary and that demography, since its beginnings, has subscribed to the classical scientific research programme launched by the promoters of modern science. Next, we examine how simulation modelling developing in population sciences recently, may help to respond to three main challenges: how to overcome complexity in social research; how to reduce its uncertainty; and how to reinforce its theoretical foundations. We sketch a model-based research programme for demography, looking specifically at interactions between various population systems. We then show how this approach might conform to the classical scientific research programme, in order to take advantage of its benefits.

Robustness in artificial life

Finding robust explanations of behaviours in Alife and related fields is made difficult by the lack of any formalised definition of robustness. A concerted effort to develop a framework which allows for robust explanations of those behaviours to be developed is needed, as well as a discussion of what constitutes a potentially useful definition for behavioural robustness. To this end, we describe two senses of robustness: robustness in systems; and robustness in explanation. We then propose a framework for developing robust explanations using linked sets of models, and describe a programme of research incorporating both robotics and chemical experiments which is designed to investigate robustness in systems.

Semi-Artificial Models of Populations: Connecting Demography with Agent-Based Modelling

In this paper we present an agent-based model of the dynamics of mortality, fertility, and partnership formation in a closed population. Our goal is to bridge the methodological and conceptual gaps that remain between demography and agent-based social simulation approaches. The model construction incorporates elements of both perspectives, with demography contributing empirical data on population dynamics, subsequently embedded in an agent-based model situated on a 2D grid space. While taking inspiration from previous work applying agent-based simulation methodologies to demography, we extend this basic concept to a complete model of population change, which includes spatial elements as well as additional agent properties. Given the connection to empirical work based on demographic data for the United Kingdom, this model allows us to analyse population dynamics on several levels, from the individual, to the household, and to the whole simulated population. We propose that such an approach bolsters the strength of demographic analysis, adding additional explanatory power.

Simulating the cost of social care in an ageing population.

In this paper we present an agent-based model of the ageing UK population. The goal of this model is to integrate statistical demographic projections of the UK population with an agent-based platform that allows us to examine the interaction between population change and the cost of social care in an ageing population. The model captures the basic processes which affect the demand for and supply of social care, including fertility, mortality, health status, and partnership formation and dissolution. The mortality and fertility rates in this population are drawn from statistical demographic projections until 2050 based on UK population data from 1951-2011. Results show that, in general, we expect the cost of social care in the UK to rise significantly as the population continues to age. An in-depth sensitivity analysis performed using Gaussian Process Emulators confirms that the level of care need within the population and the age of retirement have the most profound impact on the projected cost of social care.

Methodological Investigations in Agent-Based Modelling: With Applications for the Social Sciences

This open access book examines the methodological complications of using complexity science concepts within the social science domain. The opening chapters take the reader on a tour through the development of simulation methodologies in the fields of artificial life and population biology, then demonstrates the growing popularity and relevance of these methods in the social sciences. Following an in-depth analysis of the potential impact of these methods on social science and social theory, the text provides substantive examples of the application of agent-based models in the field of demography. This work offers a unique combination of applied simulation work and substantive, in-depth philosophical analysis, and as such has potential appeal for specialist social scientists, complex systems scientists, and philosophers of science interested in the methodology of simulation and the practice of interdisciplinary computing research.​