In the Hamadryas baboon, males are substantially larger than females. A troop of baboons is subdivided into a number of ‘one-male groups’, consisting of one adult male and one or more females with their young. The male prevents any of ‘his’ females from moving too far from him. Kummer (1971) performed the following experiment. Two males, A and B, previously unknown to each other, were placed in a large enclosure. Male A was free to move about the enclosure, but male B was shut in a small cage, from which he could observe A but not interfere. A female, unknown to both males, was then placed in the enclosure. Within 20 minutes male A had persuaded the female to accept his ownership. Male B was then released into the open enclosure. Instead of challenging male A , B avoided any contact, accepting A’s ownership.

Evolution and the Theory of Games

Software engineering: theory and practice

A review of The Symbolic Species: The Co-Evolution of Language and the Brain, by Terrance Deacon, 1997. New York: W.W. Norton, 527pp. ISBN 0393317544. $29.95 USD. Hardcover.

https://journals.library.ualberta.ca/complicity/index.php/complicity/article/download/8719/7039

The Symbolic Species: The Co-Evolution of Language and the Brain

How monkeys see the world: Inside the mind of another species

Simulating cancer growth with multiscale agent-based modeling

Simulation model validation and its rigorous assessment is known to be a difficult task. Quantification of validation is necessary to answer the question "how much validation is adequate?" One can answer this question by developing adequacy criteria to measure the validation performed on a simulation model. Developing test adequacy criteria for verifying computer programs has been useful for improving the quality and increasing confidence of regular software systems. We argue that from the validation and verification (V&V) perspective, simulation models are no different than software that are generally termed as "non-testable" due to the absence of a test oracle. There has been little research to develop V&V related adequacy criteria for this type of software. We present a validation coverage criterion, show in detail how it applies to discrete-event simulation models (DES), and discuss how it can be extended to develop V&V coverage criteria for other "non-testable" software.

/pdf/quantifying-validation-of-discrete-event-simulation-models-vaked1amff.pdf

Quantifying validation of discrete event simulation models

Although verification and validation have been studied for modeling and simulation for many decades, we do not yet have a quantitative measure of the level of validation performed on a simulation model. Validation is especially important as it determines whether or not the results from the simulation model can be trusted and used to make statements about the studied system. We propose a validation coverage metric to quantify the validation performed on a simulation model based on the possible validation that could be performed on it. This metric takes into account the aspects of the simulation model that should be validated. To show how such a metric could be utilized, we propose a version of the metric specific to agent-based models, and analyze three example models. We find that the coverage metric can be used to quantify validation on a variety of simulation models.

/pdf/a-framework-for-simulation-validation-coverage-4il5hu60at.pdf

A framework for simulation validation coverage

Effective validation of complex simulation models is often very difficult, especially when data does not exist to perform result validation through comparison of outputs of a simulation run against the real world. This situation is similar to the problem faced during verification of computer programs for which there does not exist an "oracle" to test correctness of the output. Software Engineering researchers have developed an alternate technique known as metamorphic testing, that uses a set of related input-output combinations called "pseudooracles." We propose a modified version of metamorphic testing that can be applied for simulation model validation, called metamorphic validation. Our new approach can be highly effective in building confidence toward establishing the validity of complex simulation models through the systematic process of discovery and application of metamorphic relations. We present the detailed process for applying this technique on agent-based simulations. We then utilize a case-study to show the successful application of metamorphic validation for validating a previously published multi-scale agent-based model of cancer.

Metamorphic validation for agent-based simulation models

Model validation is an inherently difficult task, as we often lack an oracle that defines correct behavior. Without an oracle it is difficult to apply results validation to determine if the model matches the system being studied. Although there are other techniques that do not require an oracle, they are not considered to be as powerful as results validation. In this paper we describe a new validation technique called "metamorphic testing" that creates pseudo-oracles to combat this problem. This technique is based on the software verification technique of the same name, which we extend to apply to validating simulation models.

Megan Olsen

Papers

Quantifying validation of discrete event simulation models

A framework for simulation validation coverage

Metamorphic validation for agent-based simulation models

Simulation validation using metamorphic testing (WIP)

Co-evolution in predator prey through reinforcement learning