We construct an agent-based model to investigate and understand the roles of green attachment, engagement in local ecological investment (i.e., greening), and social feedback.

The model includes different formulations how agents make decisions in irrigation games and this is compared with empirical data. The aim is to test different theoretical models, especially explaining effect of communication.

The model explores the emergence of inequality in cognitive and socio-emotional skills at the societal level within and across generations that results from differences in parental investment behavior during childhood and adolescence.

The network-based trust game is a hybridization of both the repeated trust games and the network games.

This model allows for analyzing the most efficient levers for enhancing the use of recycled construction materials, and the role of empirically based decision parameters.

Must tax-benefit policy making be limited to the ‘experts’?

This model explores the effects of agent interaction, information feedback, and adaptive learning in repeated auctions for farmland. It gathers information for three types of sealed-bid auctions, and one English auction and compares the auctions on the basis of several measures, including efficiency, price information revelation, and ability to handle repeated bidding and agent learning.

This model can be used to explore under which conditions agents behave as observed in field experiments on irrigation games.

This is version 1 of the Parental Investment Model by Aktipis & Fernandez-Duque.

Agent-based model using Blanche software 4.6.5. Blanche software is included in the dataset file.