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Updated: Mar 27, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
Published on: March 1, 2022
Exploring stochasticity and imprecise knowledge based on linear inequality constraints
Sam Subbey1,2, Benjamin Planque3,4, Ulf Lindstrøm4
1Institute of Marine Research, PB-1870, 5817, Bergen, Norway. samuels@imr.no.
Abstract:
This paper explores the stochastic dynamics of a simple foodweb system using a network model that mimics interacting species in a biosystem. It is shown that the system can be described by a set of ordinary differential equations with real-valued uncertain parameters, which satisfy a set of linear inequality constraints. The constraints restrict the solution space to a bounded convex polytope. We present results from numerical experiments to show how the stochasticity and uncertainty characterizing the system can be captured by sampling the interior of the polytope with a prescribed probability rule, using the Hit-and-Run algorithm. The examples illustrate a parsimonious approach to modeling complex biosystems under vague knowledge.
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