This spatially explicit agent-based model addresses how effective foraging radius (r_e) affects the effective size–and thus the equilibrium cultural diversity–of a structured population composed of central-place foraging groups.

The simulation model LAMDA investigates the influences of varying cognitive abilities of the decision maker on the truth-inducing effect of the Groves mechanism. Bounded rationality concepts are represented by information states and learning models.

The code contains four experiments for well-being based IMRL reward features.

This is a replication model of the matching problem including the mate search problem, which is the generalization of a traditional optimization problem.

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.

We developed an agent-based model to explore underlying mechanisms of behavioral clustering that we observed in human online shopping experiments.

This agent-based model represents a stylized inter-organizational innovation network where firms collaborate with each other in order to generate novel organizational knowledge.

Irrigation game calibrated on experimental data

This is a simulation model of an intelligent agent that has the objective to learn sustainable management of a renewable resource, such as a fish stock.

This model studies the effect of the agents’ adaptive expectation on cooperation frequency in the prisoner’s dilemma game in complex networks from an agent based approach. The model is implemented in Repast simphony 1.2.