The Olympic Peninsula ABM works as a virtual laboratory to simulate the existing forestland management practices as followed by different forestland owner groups in the Olympic Peninsula, Washington, and explore how they could shape the future provisions of multifunctional ecosystem services such as Carbon storage and revenue generation under the business-as-usual scenario as well as by their adaptation to interventions. Forestlands are socio-ecological systems that interact with economic, socio-cultural, and policy systems. Two intervention scenarios were introduced in this model to simulate the adaptation of landowner behavior and test the efficacy of policy instruments in promoting sustainable forest practices and fostering Carbon storage and revenue generation. (1) A market-linked carbon offset scheme that pays the forestland owners a financial incentive in the form of a yearly carbon rent. (2) An institutional intervention policy that allows small forest owners (SFLO) to cooperate for increased market access and benefits under carbon rent scenario. The model incorporates the heterogeneous contexts within which the forestland owners operate and make their forest management decisions by parameterizing relevant agent attributes and contextualizing their unique decision-making processes.

First version of the model “Neminem laedere. Socially damaging behaviours and how to contain them” by Domenico Parisi and Nicola Lettieri

An agent-based model of species interaction on fragmented landscape is developed to address the question, how do population levels of predators and prey react with respect to changes in the patch connectivity as well as changes in the sharpness of threshold dispersal?

The model uses opinion dynamics to test a simple and ecient but empirically based approach for generating social networks in spatial agent-based models which explicitly takes into account restrictions and opportunities imposed by effects of baseline homophily and considers the probability of links that depends on geographical distance between potential partners.

This agent-based model examines the impact of seasonal aggregation, dispersion, and learning opportunities on the richness and evenness of artifact styles under random social learning (unbiased transmission).

This purpose of this model is to understand how the coupled demographic dynamics of herds and households constrain the growth of livestock populations in pastoral systems.

Agent-based models of organizational search have long investigated how exploitative and exploratory behaviors shape and affect performance on complex landscapes. To explore this further, we build a series of models where agents have different levels of expertise and cognitive capabilities, so they must rely on each other’s knowledge to navigate the landscape. Model A investigates performance results for efficient and inefficient networks. Building on Model B, it adds individual-level cognitive diversity and interaction based on knowledge similarity. Model C then explores the performance implications of coordination spaces. Results show that totally connected networks outperform both hierarchical and clustered network structures when there are clear signals to detect neighbor performance. However, this pattern is reversed when agents must rely on experiential search and follow a path-dependent exploration pattern.

This model proposes a new approach analyzing to the doctrinal paradox by considering a deliberative process (which can be represented by an agent-based model) in comparison with classical (binary) majority voting and an aggregation of (continuous) degrees of belief prior to majority voting. This model is a multivariate extension of the Hegselmann–Krause opinion dynamics model.

The model simulates interaction between internal physiological factors (e.g. energy balance) and external social factors (e.g. competition level) underlying feeding and social interaction behaviour of commercially group-housed pigs.

The model presented here was created as part of my dissertation. It aims to study the impacts of topography and climate change on prehistoric networks, with a focus on the Magdalenian, which is dated to between 20 and 14,000 years ago.