Computational Model Library

Displaying 10 of 329 results for "Daniel J Singer" clear search

A model of groundwater usage by farmers in the Upper Guadiana, Spain

Georg Holtz | Published Thursday, June 30, 2011 | Last modified Saturday, April 27, 2013

An agent-based model to investigate the history of irrigated agriculture in the Upper Guadiana Basin, Spain, in order to learn about the influence of farmers’ characteristics (inter alia profit orientation, risk aversion, skills, available labour force and farm size) on land-use change and associated groundwater over-use in this region.

LimnoSES - social-ecological lake management undergoing regime shifts

Romina Martin | Published Thursday, November 24, 2016 | Last modified Friday, January 18, 2019

LimnoSES is a coupled system dynamics, agent-based model to simulate social-ecological feedbacks in shallow lake use and management.

Knowledge Based Economy (KBE) is an artificial economy where firms placed in geographical space develop original knowledge, imitate one another and eventually recombine pieces of knowledge. In KBE, consumer value arises from the capability of certain pieces of knowledge to bridge between existing items (e.g., Steve Jobs illustrated the first smartphone explaining that you could make a call with it, but also listen to music and navigate the Internet). Since KBE includes a mechanism for the generation of value, it works without utility functions and does not need to model market exchanges.

An agent-based framework that aggregates social network-level individual interactions to run targeting and rewarding programs for a freemium social app. Git source code in https://bitbucket.org/mchserrano/socialdynamicsfreemiumapps

This model is used to simulate the influence of spatially and temporally variable sedimentary processes on the distribution of dated archaeological features in a surface context.

Cultural transmission in structured populations

Luke Premo | Published Wednesday, November 13, 2024

This structured population model is built to address how migration (or intergroup cultural transmission), copying error, and time-averaging affect regional variation in a single selectively neutral discrete cultural trait under different mechanisms of cultural transmission. The model allows one to quantify cultural differentiation between groups within a structured population (at equilibrium) as well as between regional assemblages of time-averaged archaeological material at two different temporal scales (1,000 and 10,000 ticks). The archaeological assemblages begin to accumulate only after a “burn-in” period of 10,000 ticks. The model includes two different representations of copying error: the infinite variants model of copying error and the finite model of copying error. The model also allows the user to set the variant ceiling value for the trait in the case of the finite model of copying error.

This model is programmed in Python 3.6. We model how different consensus protocols and trade network topologies affect the performance of a blockchain system. The model consists of multiple trader and miner agents (Trader.py and Tx.py), and one system agent (System.py). We investigated three consensus protocols, namely proof-of-work (PoW), proof-of-stake (PoS), and delegated proof-of-stake (DPoS). We also examined three common trade network topologies: random, small-world, and scale-free. To reproduce our results, you may need to create some databases using, e.g., MySQL; or read and write some CSV files as model configurations.

The community consequences of intra-specific trait variation (ITV) are a current topic in ecological research. The effects of ITV on species coexistence have, yet, not sufficiently been understood. With this individual-based model we analyzed the effect of intra-specific variation in movement by mimicking variation found in ground-dwelling rodents and analyzing how such variation affects inter-specific differences in competitive ability (i.e. foraging efficiency) and temporary coexistence. The movement algorithm and behavioral plasticity was adapted from existing algorithms and current ecological literature. As a measure for temporary coexistence, we analyzed the time until one of the species went extinct.

In this paper we introduce an agent-based model of elections and government formation where voters do not have perfect knowledge about the parties’ ideological position. Although voters are boundedly rational, they are forward-looking in that they try to assess the likely impact of the different parties over the resulting government. Thus, their decision rules combine sincere and strategic voting: they form preferences about the different parties but deem some of them as inadmissible and try to block them from office. We find that the most stable and durable coalition governments emerge at intermediate levels of informational ambiguity. When voters have very poor information about the parties, their votes are scattered too widely, preventing the emergence of robust majorities. But also, voters with highly precise perceptions about the parties will cluster around tiny electoral niches with a similar aggregate effect.

The purpose of the model is to generate coalition structures of different glove games, using a specially designed algorithm. The coalition structures can be are later analyzed by comparing them to core partitions of the game used. Core partitions are coalition structures where no subset of players has an incentive to form a new coalition.

The algorithm used in this model is an advancement of the algorithm found in Collins & Frydenlund (2018). It was used used to generate the results in Vernon-Bido & Collins (2021).

Displaying 10 of 329 results for "Daniel J Singer" clear search

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