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From Roy Bhaskar et al Book Interdisciplinarity and climate change: transforming knowledge and practice for our global future

Critical Realism

Geoff McDonnell

4 days ago

This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

A decent match to the data is made with
Wolf Death Rate = 0.15
Wolf Birth Rate Factor = 0.0203
Moose Death Rate Factor = 1.08
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is MBR*M*(1-M/K)
Moose death flow is MDRF*Sqrt(M*W)
Wolf birth flow is WBRF*Sqrt(M*W)
Wolf death flow is WDR*W

A More Realistic Model of Isle Royale: Predator Prey Interactions

Andrew E Long

83

Final Group Formula 1 Model

Abdurehman Ahmad

4

Simulate an impact of an asteroid of any Diameter at any given Speed!

Asteroid impact simulator

Alex Neroni

9 months ago

In this model we seek to show how Formula 1 can bring there Co2 emissions down to zero by 2030 (six years from now).

Formula 1 Model

Yasamin Osmani

WIP Summary of the History of Pragmatism mostly based on Cheryl Misak's Books insight integrated with Cornelis de Waal's Introducing Pragmatism insight See also Insight Misak Peircean Truth and the end of Inquiry

History of Pragmatism

Geoff McDonnell

13 hours ago

Simple box model for atmospheric and ocean carbon cycle, with surface and deep water, including DIC system, carbonate alkalinity, weathering, O2, and PO4 feedbacks.

Lab 10 (predictive model eg. keeling curve)

Alec Phipps

3

BSRD model 3.0

Adam Bouche

9

Problem 3 - Instagram

Bao N

This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

Experiment with adjusting the initial number of moose and wolves on the island.

Day 22: More Realistic Model of Isle Royale: Predator Prey Interactions

Jacob Englert

Hoffman and Klein IEEE Intelligent systems 2017-18 series of articles on decision making and computing, including macrocognition

1 theoretical foundations abstract

2 empirical foundations abstract

3 causal landscapes abstract

4 deep nets abstract

See also 2018 Gary Klein podcast and the process of explaining insight

Explaining Explanation

Geoff McDonnell

This model simulates the tradeoff between the total costs and total benefits of using AI. The model shows the investment rate in comparison to the effectiveness and efficiency rate of the AI and we can visualize this relationship with our graph to see the cost and benefits of AI.

AI

Roman Ahmad zeia

Realistic Teaching Tool

Sarah Marshall

Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.

With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.

We start with an SIR model, such as that featured in the MAA model featured in

https://www.maa.org/press/periodicals/loci/joma/the-sir-model-for-spread-of-disease-the-differential-equation-model

Without mortality, with time measured in days, with infection rate 1/2, recovery rate 1/3, and initial infectious population I_0=1.27x10-4, we reproduce their figure

With a death rate of .005 (one two-hundredth of the infected per day), an infectivity rate of 0.5, and a recovery rate of .145 or so (takes about a week to recover), we get some pretty significant losses -- about 3.2% of the total population.

Resources:

Coronavirus: A Simple SIR (Susceptible, Infected, Recovered) with death

Andrew E Long

62

Realistic Teaching Tool

Ian Youngkin

Improvement Science as one of the clusters of interacting methods for improving health services network design and delivery using complex decision technologies IM-17952

Improvement Science

Geoff McDonnell

Realistic teaching tool

Brittany Partee

Realistic Teaching Tool

Sage K Quiggle

Modified from Sterman (2006) article and Gene Bellinger's Assumptions IM-351 by Dr Rosemarie Sadsad UNSW See also Complex Decision Technologies IM and IM-63975

Virtual Experiments

Geoff McDonnell

3 9 months ago

This simulation allows you to compare different approaches to influence flow, the Flow Times and the throughput of a work process. The simulation is described in the blog post "Starting late - The Superior Scheduling Approach - How, despite being identical, one company delivers almost 10 times the value of its competitor using flow-oriented project initiation."

By adjusting the slider below you can observe the work process

without any work in process limitations (WIP Limits),
with process step specific WIP Limits* (work state WIP limits),
with Kanban Token and Replenishment Token based on the Tameflow approach (a form of drum-buffer-rope)
with Drum Buffer Rope** scheduling method.

* Well know in (agile) Kanban

** Known in the physical world of factory production

The simulation and the comparison between the different scheduling approaches can be seen here -> https://youtu.be/xXvdVkxeMMQ

The "Tameflow approach" using Kanban Token and Replenishment Token as well as the Drum Buffer Rope method take the Constraint (the weakest link of the work process) into consideration when pulling in new work items into the delivery "system".

Feel free to play around and recognize the different effects of work scheduling methods.

If you have questions or feedback get in touch via twitter @swilluda

The work flow itself

Look at the simulation as if you would look on a kanban board.

The simulation mimics a "typical" feature delivery process on portfolio level.

From left to right you find the following ten process steps.