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

This model describes the consequences of limited vision of agents in harvesting a common resource. We show the vulnerability of cooperation due to reduced visibility of the resource and other agents.

The model represents an archetypical fishery in a co-evolutionary social-ecological environment, capturing different dimensions of trust between fishers and fish buyers for the establishment and persistence of self-governance arrangements.

IDEAL: Agent-Based Model of Residential Land Use Change where the choice of new residential development in based on the Ideal-point decision rule.

SeaROOTS ABM is a quite generic agent-based modeling system, for simulating and evaluating potential terrestrial and maritime mobility of artificial hominin groups, configured by available archaeological data and hypotheses. Necessary bathymetric, geomorphological and paleoenvironmental data are combined in order to reconstruct paleoshorelines for the study area and produce an archaeologically significant agent environment. Paleoclimatic and archaeological data are incorporated in the ABM in order to simulate maritime crossings and assess the emergent patterns of interaction between human agency and the sea.

SeaROOTS agent-based system includes completely autonomous, utility-based agents (Chliaoutakis & Chalkiadakis 2016), representing artificial hominin groups, with partial knowledge of their environment, for simulating their evolution and potential maritime mobility, utilizing alternative Least Cost Path analysis modeling techniques (Gustas & Supernant 2017, Gravel-Miguel & Wren 2021). Two groups of hominins, Neanderthals and Homo sapiens, are chosen in order to study the challenges and actions employed as a response to the fluctuating sea-levels, as well as probability scenarios with respect to sea-crossings via buoyant vessels (rafting) or the human body itself (swimming). SeaROOTS ABM aims to simulate various scenarios and investigate the degree climatic fluctuations influenced such activities and interactions in the Middle Paleolithic period.

The model focuses on simulating potential terrestrial and maritime routes, explore the interactions and relations between autonomous agents and their environment, as well as to test specific research questions; for example, when and under what conditions would Middle Paleolithic hominins be more likely to attempt a crossing and successfully reach the islands? By which agent type (Sapiens or Neanderthals) and how (e.g. swimming or by sea-vessels) could such short sea crossings be (mostly) attempted, and which (sea) routes were usually considered by the agents? When does a sea-crossing become a choice and when is it a result of forced migration, i.e. disaster- or conflict-induced displacement? Results show that the dynamic marine environment of the Inner Ionian, our case study in this work, played an important role in their decision-making process.

This is an agent-based model of peer review built on the following three entities: papers, scientists and conferences. The model has been implemented on a BDI platform (Jason) that allows to perform both parameter and mechanism exploration.

We develop a spatial, evolutionary model of the endogenous formation and dissolution of groups using a renewable common pool resource. We use this foundation to measure the evolutionary pressures at different organizational levels.

An Agent-Based Model to simulate agent reactions to threatening information based on the anxiety-to-approach framework of Jonas et al. (2014).
The model showcases the framework of BIS/BAS (inhibitory and approach motivated behavior) for the case of climate information, including parameters for anxiety, environmental awareness, climate scepticism and pro-environmental behavior intention.

Agents receive external information according to threat-level and information frequency. The population dynamic is based on the learning from that information as well as social contagion mechanisms through a scale-free network topology.

The model uses Netlogo 6.2 and the network extension.
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This is a multi-patch meta-population ecological model. It intended as a test-bed in which to test the impact of humans with different kinds of social structure.

The HUMan Impact on LANDscapes (HUMLAND) 2.0.0 is an enhanced version of HUMLAND 1.0.0, developed to track and quantify the intensity of various impacts on landscapes at a continental scale. The model is designed to identify the most influential factors in the transformation of interglacial vegetation, with a particular focus on the burning practices of hunter-gatherers. HUMLAND 2.0.0 incorporates a wide range of spatial datasets as both inputs and targets (expected modelling results) for simulations across Last Interglacial (~130,000–116,000 BP) and Early Holocene (~11,700–8,000 BP).