Agent-based model of hunting behavior of Ache hunter-gatherers from Paraguay. We evaluate the effect of group size and cooperative hunting

Agent-Based-Modeling - space colonization
ask me for the .nlogo model
WHAT IS IT?
The goal of this project is to simulate with NetLogo (v6.2) a space colonization of humans, starting from Earth, into the Milky Way.

HOW IT WORKS
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The SimPioN model aims to abstractly reproduce and experiment with the conditions under which a path-dependent process may lead to a (structural) network lock-in in interorganisational networks.

Path dependence theory is constructed around a process argumentation regarding three main elements: a situation of (at least) initially non-ergodic (unpredictable with regard to outcome) starting conditions in a social setting; these become reinforced by the workings of (at least) one positive feedback mechanism that increasingly reduces the scope of conceivable alternative choices; and that process finally results in a situation of lock-in, where any alternatives outside the already adopted options become essentially impossible or too costly to pursue despite (ostensibly) better options theoretically being available.

The purpose of SimPioN is to advance our understanding of lock-ins arising in interorganisational networks based on the network dynamics involving the mechanism of social capital. This mechanism and the lock-ins it may drive have been shown above to produce problematic consequences for firms in terms of a loss of organisational autonomy and strategic flexibility, especially in high-tech knowledge-intensive industries that rely heavily on network organising.

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We present here MEGADAPT_SESMO model. A hybrid, dynamic, spatially explicit, integrated model to simulate the vulnerability of urban coupled socio-ecological systems – in our case, the vulnerability of Mexico City to socio-hydrological risk.

This model explores different aspects of the formation of urban neighbourhoods where residents believe in values distant from those dominant in society. Or, at least, this is what the Danish government beliefs when they discuss their politics about parallel societies. This simulation is set to understand (a) whether these alternative values areas form and what determines their formation, (b) if they are linked to low or no income residents, and (c) what happens if they disappear from the map. All these three points are part of the Danish government policy. This agent-based model is set to understand the boundaries and effects of this policy.

Contains python3 code to replicate the opinion dynamics model from our (so far unpublished) JASSS sumbission “A Balance Model of Opinion Hyperpolarization”. The main function is run_model(), which returns a dictionary object containing various outcome metrics.

This is an agent-based model that captures the dynamic processes related to moving from an educational system where the school a student attends is based on assignment to a neighborhood school, to one that gives households more choice among existing and newly formed public schools.

We used our model to test how different combinations of dominance interactions present in H. saltator could result in linear, despotic, or shared hierarchies.

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

Our Hybrid Climate Assessment Model (HCAM) aims to simulate the behaviours of individuals under the influence of climate change and external policy makings. In our proposed solution we use System Dynamics (SD) modelling to represent the physical and economic environments. Agent-Based (AB) modelling is used to represent collections of individuals that can interact with other collections of individuals and the environment. In turn, individual agents are endowed with an internal SD model to track their psychological state used for decision making. In this paper we address the feasibility of such a scalable hybrid approach as a proof-of-concept. This novel approach allows us to reuse existing rigid, but well-established Integrated Assessment Models (IAMs), and adds more flexibility by replacing aggregate stocks with a community of vibrant interacting entities.

Our illustrative example takes the settings of the U.S., a country that contributes to the majority of the global carbon footprints and that is the largest economic power in the world. The model considers the carbon emission dynamics of individual states and its relevant economic impacts on the nation over time.

Please note that the focus of the model is on a methodological advance rather than on applying it for predictive purposes! More details about the HCAM are provided in the forthcoming JASSS paper “An Innovative Approach to Multi-Method Integrated Assessment Modelling of Global Climate Change”, which is available upon request from the authors (contact peer-olaf.siebers@nottingham.ac.uk).