This research article presents an agent-based simulation hereinafter called COMMONSIM. It builds on COMMONISM, i.e. a large-scale commons-based vision for a utopian society. In this society, production and distribution of means are not coordinated via markets, exchange, and money, or a central polity, but via bottom-up signalling and polycentric networks, i.e. ex-ante coordination via needs. Heterogeneous agents care for each other in life groups and produce in different groups care, environmental as well as intermediate and final means to satisfy sensual-vital needs. Productive needs decide on the magnitude of activity in groups for a common interest, e.g. the production of means in a multi-sectoral artificial economy. Agents share cultural traits identified by different behaviour: a propensity for egoism, leisure, environmentalism, and productivity. The narrative of this utopian society follows principles of critical psychology and sociology, complexity and evolution, the theory of commons, and critical political economy. The article presents the utopia and an agent-based study of it, with emphasis on culture-dependent allocation mechanisms and their social and economic implications for agents and groups.

This model is designed to investigate the impact of alternative policy approaches and changing land tenure dynamics on farmer adoption of conservation practices intended to increase the water quality.

This model is a replication of Torsten Hägerstrand’s 1965 model–one of the earliest known calibrated and validated simulations with implicit “agent based” methodology.

Emulation is one of the simplest and most common mechanisms of social interaction. In this paper we introduce a descriptive computational model that attempts to capture the underlying dynamics of social processes led by emulation.

A model to show the effects of flood risk on a housing market; the role of flood protection for risk reduction; the working of the existing public-private flood insurance partnership in the UK, and the proposed scheme ‘Flood Re’.

This model simulates the heterogeneity of preferences in a PG game and how the interaction between them affects the dynamics of voluntary contributions. Model is based on the results of a human-based experiment.

Signaling chains are a special case of Lewis’ signaling games on networks. In a signaling chain, a sender tries to send a single unit of information to a receiver through a chain of players that do not share a common signaling system.

This model investigates the link between prescribed growth in body size, population dynamics and density dependence through population feedback on available resources.

Status-power dynamics on a playground, resulting in a status landscape with a gender status gap. Causal: individual (beauty, kindness, power), binary (rough-and-tumble; has-been-nice) or prior popularity (status). Cultural: acceptability of fighting.

A model of innovation diffusion in a structured population with two groups who are averse to adopting a produce popular with the outgroup.