Modeling 101 - Revision history

Rsalter: /* Agent Based Models */

2018-01-28T18:19:10Z

Agent Based Models

← Older revision		Revision as of 18:19, 28 January 2018
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	Agent based models study the interaction of objects in space. Agents are objects with a specific set of rules, and can represent anything from ants to grains of sand. They move and interact in a simulated region of space. The interaction between the Agents, and sometimes their interaction with the landscape, are the core of this field. In some ways an Agent Based model is similar to Spatial Model, but unlike a Cell an Agent has no neighbors and it's position is not fixed.		Agent based models study the interaction of objects in space. Agents are objects with a specific set of rules, and can represent anything from ants to grains of sand. They move and interact in a simulated region of space. The interaction between the Agents, and sometimes their interaction with the landscape, are the core of this field. In some ways an Agent Based model is similar to Spatial Model, but unlike a Cell an Agent has no neighbors and it's position is not fixed.

	Agent Based Models are a useful tool for describing how complex behavior emerges from the interactions of the individual components. The classic agent based model is a flock of birds organizing itself based on the simple rules followed by each agent. Numerus includes a number of examples including ~~the Game of Life,~~ the SIR model, and Antz.		Agent Based Models are a useful tool for describing how complex behavior emerges from the interactions of the individual components. The classic agent based model is a flock of birds organizing itself based on the simple rules followed by each agent. Numerus includes a number of examples including the SIR model, and Antz.

	===Advantages and Disadvantages===		===Advantages and Disadvantages===

Rsalter: /* The Fundamentals of Computational Modeling */

2018-01-20T21:44:06Z

The Fundamentals of Computational Modeling

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	Another goal of modeling can be to test a hypothesis. This is because what a model fails to predict can be just as revealing as what it does. If the model of a system behaves differently than the real data it is compared too, this means that our understanding of the model is incomplete. As an example, a model indicates that the prey population should be stable but the data indicates it is plummeting. This could indicate many things, whether a predator or disease or lowered birthrate. But clearly there is something strange going on that requires investigation.		Another goal of modeling can be to test a hypothesis. This is because what a model fails to predict can be just as revealing as what it does. If the model of a system behaves differently than the real data it is compared too, this means that our understanding of the model is incomplete. As an example, a model indicates that the prey population should be stable but the data indicates it is plummeting. This could indicate many things, whether a predator or disease or lowered birthrate. But clearly there is something strange going on that requires investigation.

	Hopefully this brief introduction to the field of Computation Modeling has given you a sense of it's versatility and applicability. The rest of this introduction will focus on the three primary specialties of Numerus: Dynamical Systems Models, Spatial Models, and Network Models.		Hopefully this brief introduction to the field of Computation Modeling has given you a sense of it's versatility and applicability. The rest of this introduction will focus on the three primary specialties of Numerus: Dynamical Systems Models, Spatial Models, Agent-based Models, and Network Models.

	==Dynamical System Models==		==Dynamical System Models==

Rsalter at 21:40, 20 January 2018

2018-01-20T21:40:45Z

← Older revision		Revision as of 21:40, 20 January 2018
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	Another goal of modeling can be to test a hypothesis. This is because what a model fails to predict can be just as revealing as what it does. If the model of a system behaves differently than the real data it is compared too, this means that our understanding of the model is incomplete. As an example, a model indicates that the prey population should be stable but the data indicates it is plummeting. This could indicate many things, whether a predator or disease or lowered birthrate. But clearly there is something strange going on that requires investigation.		Another goal of modeling can be to test a hypothesis. This is because what a model fails to predict can be just as revealing as what it does. If the model of a system behaves differently than the real data it is compared too, this means that our understanding of the model is incomplete. As an example, a model indicates that the prey population should be stable but the data indicates it is plummeting. This could indicate many things, whether a predator or disease or lowered birthrate. But clearly there is something strange going on that requires investigation.

	Hopefully this brief introduction to the field of Computation Modeling has given you a sense of it's versatility and applicability. The rest of this introduction will focus on the three primary specialties of ~~NumerusMB~~: Dynamical Systems Models, Spatial Models, and Network Models.		Hopefully this brief introduction to the field of Computation Modeling has given you a sense of it's versatility and applicability. The rest of this introduction will focus on the three primary specialties of Numerus: Dynamical Systems Models, Spatial Models, and Network Models.

	==Dynamical System Models==		==Dynamical System Models==
	Dynamical system models represent systems that change over time. Typical examples include a population of organisms, the flow of money in the economy, or a manufacturing process. What each of these diverse ‘systems’ have in common is that they change over time.		Dynamical system models represent systems that change over time. Typical examples include a population of organisms, the flow of money in the economy, or a manufacturing process. What each of these diverse ‘systems’ have in common is that they change over time.

	At the heart of a dynamical system model is a set of rules and equations that reflect how the system changes in a particular instant. By rendering these rules in a simulation program like ~~NumerusMB~~ and letting it run, you can see how these momentary changes lead the system to develop.		At the heart of a dynamical system model is a set of rules and equations that reflect how the system changes in a particular instant. By rendering these rules in a simulation program like Numerus and letting it run, you can see how these momentary changes lead the system to develop.

	===Goals of Developing Dynamical Systems Models===		===Goals of Developing Dynamical Systems Models===
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	Agent based models study the interaction of objects in space. Agents are objects with a specific set of rules, and can represent anything from ants to grains of sand. They move and interact in a simulated region of space. The interaction between the Agents, and sometimes their interaction with the landscape, are the core of this field. In some ways an Agent Based model is similar to Spatial Model, but unlike a Cell an Agent has no neighbors and it's position is not fixed.		Agent based models study the interaction of objects in space. Agents are objects with a specific set of rules, and can represent anything from ants to grains of sand. They move and interact in a simulated region of space. The interaction between the Agents, and sometimes their interaction with the landscape, are the core of this field. In some ways an Agent Based model is similar to Spatial Model, but unlike a Cell an Agent has no neighbors and it's position is not fixed.

	Agent Based Models are a useful tool for describing how complex behavior emerges from the interactions of the individual components. The classic agent based model is a flock of birds organizing itself based on the simple rules followed by each agent. ~~NumerusMB~~ includes a number of examples including the Game of Life, the SIR model, and Antz.		Agent Based Models are a useful tool for describing how complex behavior emerges from the interactions of the individual components. The classic agent based model is a flock of birds organizing itself based on the simple rules followed by each agent. Numerus includes a number of examples including the Game of Life, the SIR model, and Antz.

	===Advantages and Disadvantages===		===Advantages and Disadvantages===

Rsalter at 21:33, 20 January 2018

2018-01-20T21:33:55Z

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	===Goals of Developing Dynamical Systems Models===		===Goals of Developing Dynamical Systems Models===
	Dynamical Systems Models are used to describe when something you are measuring moves from one place to another, or transforms from one thing to something else. This may be modelling the flow of Carbon between various reservoirs, or it may be modeling the different cohorts in a population as they age. It can even represent the flow between sick and infected populations. The key point is that you have a measurable quantity being shuffled between categories without being lost in the transfer.		Dynamical Systems Models are used to describe when something you are measuring moves from one place to another, or transforms from one thing to something else. This may be modelling the flow of Carbon between various reservoirs, or it may be modeling the different cohorts in a population as they age. It can even represent the flow between sick and infected populations. The key point is that you have a measurable quantity being shuffled between categories without being lost in the transfer.

	~~===Dynamical Systems Models in NumerusMB===~~
	In NumerusMD we use the Stock and Flow objects. Stocks represent a pool of what we are measuring: infected population, nitrogen in lake water, and so on. Flows represent the movement of what we are measuring from one stock to another. This would be the flow of people from uninfected to infected population, or nitrogen from lake water to the algae population. Flows can also represent a source or sink of our measured quantity. A Source flow could represent immigration and births adding people, while a Sink flow would could represent people's deaths. Similarly a Source for nitrogen could represent runoff from farmland.

	==Spatial Models==		==Spatial Models==
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	===Goals of Developing Spatial Models===		===Goals of Developing Spatial Models===
	Spatial models are, obviously enough, used for studying the behavior of entire landscapes. They can address the population density of a city, and misbehavior in a classroom, or the interaction between plant cover rainfall and wildfire. However it is important to note that the landscape can be metaphorical. The key requirement for a Spatial Model is simply that each cell has a fixed distance from each by some metric, and that the cells interact with each other. A Spatial Model can also provide critical context for an Agent Based model. In a model of honeybee behavior and pollination, for example, the bee agents will have a direct impact on the landscape and vice versa.		Spatial models are, obviously enough, used for studying the behavior of entire landscapes. They can address the population density of a city, and misbehavior in a classroom, or the interaction between plant cover rainfall and wildfire. However it is important to note that the landscape can be metaphorical. The key requirement for a Spatial Model is simply that each cell has a fixed distance from each by some metric, and that the cells interact with each other. A Spatial Model can also provide critical context for an Agent Based model. In a model of honeybee behavior and pollination, for example, the bee agents will have a direct impact on the landscape and vice versa.

	~~===Spatial Models in NumerusMB===~~
	Spatial models in NumerusMB use a CellMatrix to represent the landscape of the simulation. The Cell is the fundamental unit of analysis. A CellMatrix maintains an array of cells in either a Cartesian or Hexagonal lattice topology, in which individual cells are aware of both their location and their neighborhoods. Conway's Game of Life [citation] is an example of such a model, with the cells “alive” and “dead” depending on the state of each individual cell's neighbors. Each cell's behavior is individually programmed as a Capsule, which is then assigned to the CellMatrix.

	==Agent Based Models==		==Agent Based Models==
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	===Advantages and Disadvantages===		===Advantages and Disadvantages===
	Agent Based Models are a tool, and like any tool they are better at solving some problems and worse at solving others. They tend to be a bit harder both conceptually and practically to put together, since they have more components to them than simple analytical models. Despite this, however, they generally require a smaller base of knowledge about the system that someone is trying to model. It is easy, for example, to know that someone who is sick has a certain probability of infecting someone they interact with. It is more difficult to come up with an equation to demonstrate the rate at which someone infects other people without knowing how often they interact, how contagious they are, and whether or not people they interact with are susceptible to infection or not. In this situation, it makes sense simulate a spatial dimension in order to make up for information that is not necessarily obvious. Another situation in which agent based models shine is large systems whose group behavior is important. In the flocking model discussed above, the individual behavior of the birds is meaningless and even distracting. But when seen in the context of the larger group, important trends appear from the noise that define the model's behavior.		Agent Based Models are a tool, and like any tool they are better at solving some problems and worse at solving others. They tend to be a bit harder both conceptually and practically to put together, since they have more components to them than simple analytical models. Despite this, however, they generally require a smaller base of knowledge about the system that someone is trying to model. It is easy, for example, to know that someone who is sick has a certain probability of infecting someone they interact with. It is more difficult to come up with an equation to demonstrate the rate at which someone infects other people without knowing how often they interact, how contagious they are, and whether or not people they interact with are susceptible to infection or not. In this situation, it makes sense simulate a spatial dimension in order to make up for information that is not necessarily obvious. Another situation in which agent based models shine is large systems whose group behavior is important. In the flocking model discussed above, the individual behavior of the birds is meaningless and even distracting. But when seen in the context of the larger group, important trends appear from the noise that define the model's behavior.

	~~===Agent Based Models in NumerusMB===~~
	Agent based models in NumerusMB are models that make use of an AgentVector. The AgentVector contains the population of Agents, as well as their location. In addition, NumerusMB includes Simworlds and Networlds. A SimWorld combines an AgentVector with a CellMatrix that provides a landscape. The Networld component uses a NodeNetwork for the same purpose. The ''SIR'' model is an example of an agent vector, with agents moving about an open space in three possible states, Susceptible, Infected, and Recovered. The ''Antz'' model is a more complicated model that uses both an agent vector and a cell matrix in order to simulate how ants collect food and leave a path for other ants to follow in order to find the same food.

	NumerusMB has a lot of tools that make agent based models simpler and more robust. In particular, it is very easy to have access to all agents and cells from each individual agent, and to incorporate a wide variety of local and global effects. It also makes it simple to set up multiple Sim Worlds in order to see various outcomes simultaneously. It is also built on arrays and methods, which makes it simple to work on a small level to tweak the model to the user’s liking. On the other hand, the visual side of NumerusMB makes it so that it is easy to quickly and efficiently set up the shell of an agent based model and immediately get down to the more important details involved in the model. A savvy NumerusMB programmer will begin an agent based model visually and slowly transition over to handling the methods and functions in a more programming heavy reference frame.

	==Network Based Models==		==Network Based Models==

	===Goals of Development Network Based Models===		===Goals of Development Network Based Models===
	~~===Network Based Models in NumerusMB===~~

	==Basic Model Design in Numerus==		==Basic Model Design in Numerus==
	Click [[Modeling in Numerus\|here]] to see how these concepts are implemented in Numerus.		Click [[Modeling in Numerus\|here]] to see how these concepts are implemented in Numerus.

Rsalter: /* Basic Model Design in Numerus */

2018-01-20T21:31:01Z

Basic Model Design in Numerus

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	==Basic Model Design in Numerus==		==Basic Model Design in Numerus==
	Click [[~~Basic Model Design~~ in Numerus\|here]] to see how these concepts are implemented in Numerus.		Click [[Modeling in Numerus\|here]] to see how these concepts are implemented in Numerus.

Rsalter: /* Basic Model Design in Numerus */

2018-01-20T21:30:12Z

Basic Model Design in Numerus

← Older revision		Revision as of 21:30, 20 January 2018
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	==Basic Model Design in Numerus==		==Basic Model Design in Numerus==
	Click [[Basic Model Design in Numerus]] to see how these concepts are implemented in Numerus.		Click [[Basic Model Design in Numerus\|here]] to see how these concepts are implemented in Numerus.

Rsalter at 21:29, 20 January 2018

2018-01-20T21:29:46Z

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	===Network Based Models in NumerusMB===		===Network Based Models in NumerusMB===

	==Basic Model Design in ~~NumerusMB~~==		==Basic Model Design in Numerus==
			Click [[Basic Model Design in Numerus]] to see how these concepts are implemented in Numerus.
	It is important to grasp the extent of the NumerusMB platform in order to implement powerful and complex dynamical system and agent based models. As described above, NumerusMB provides an impressive range and versatility of components to effectively execute both Dynamic Systems and Agent Based models. In addition, NumerusMB has the capability to implement designs using specialized analysis like '''Perceptrons''' and other Neural Network prediction algorithms. To utilize NumerusMB's capabilities we must first understand the basics of NumerusMB's '''Chip''' component and '''Population Models'''.

	*Jump into NumerusMB's [[Operational_Semantics\|Operational Semantics]] here.

	*Get a run through of NumerusMB's [[Frames,_Menus,_Toolbars,_Pallets\|GUI here]].

	~~===Chip Basics===~~

	As the [[Glossary\|NumerusMB Glossary]] states, a '''Chip''' is a Container component which contains a single '''Capsule''' instance. A '''Capsule''' is a prototype for a simulation unit. It contains base components and may contain other chips, inputs, and / or outputs. These definitions may appear a bit vague or broad, however, that is simply because '''Chips''' and '''Capsules''' are widely used in a variety of ways within NumerusMB.

	~~Chip structure and usage in NumerusMB may best be understood through example.~~ Click [[~~Using_Chips:_Example\|here]] for an example of using a preexisting model (from the Model Library) and manipulating the ideas of model layers and chips.~~

	~~===Population Model 101===~~

	~~See the [[Example_1:_Simple_Population_Model\|Simple Population~~ Model]] ~~tutorial in the Model Library. This tutorial demonstrates fundamental NumerusMB usage, including how~~ to ~~operate the Graphical User Interface, or '''GUI''', and its algorithmic and mathematical design. You will~~ see ~~basic usage of the ''Modeling Canvas'' and the ''Dashboard'' as well as NumerusMB's intuitive mathematical design~~.

Iburns: /* Network Based Models */

2017-10-08T01:09:52Z

Network Based Models

← Older revision		Revision as of 01:09, 8 October 2017
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	==Network Based Models==		==Network Based Models==

			===Goals of Development Network Based Models===
	===Network Based Models in NumerusMB===		===Network Based Models in NumerusMB===
	~~===Goals of Development Network Based Models===~~

	==Basic Model Design in NumerusMB==		==Basic Model Design in NumerusMB==

Iburns: /* Dynamical Systems Models in NumerusMD */

2017-10-08T01:09:23Z

Dynamical Systems Models in NumerusMD

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	Dynamical Systems Models are used to describe when something you are measuring moves from one place to another, or transforms from one thing to something else. This may be modelling the flow of Carbon between various reservoirs, or it may be modeling the different cohorts in a population as they age. It can even represent the flow between sick and infected populations. The key point is that you have a measurable quantity being shuffled between categories without being lost in the transfer.		Dynamical Systems Models are used to describe when something you are measuring moves from one place to another, or transforms from one thing to something else. This may be modelling the flow of Carbon between various reservoirs, or it may be modeling the different cohorts in a population as they age. It can even represent the flow between sick and infected populations. The key point is that you have a measurable quantity being shuffled between categories without being lost in the transfer.

	===Dynamical Systems Models in ~~NumerusMD~~===		===Dynamical Systems Models in NumerusMB===
	In NumerusMD we use the Stock and Flow objects. Stocks represent a pool of what we are measuring: infected population, nitrogen in lake water, and so on. Flows represent the movement of what we are measuring from one stock to another. This would be the flow of people from uninfected to infected population, or nitrogen from lake water to the algae population. Flows can also represent a source or sink of our measured quantity. A Source flow could represent immigration and births adding people, while a Sink flow would could represent people's deaths. Similarly a Source for nitrogen could represent runoff from farmland.		In NumerusMD we use the Stock and Flow objects. Stocks represent a pool of what we are measuring: infected population, nitrogen in lake water, and so on. Flows represent the movement of what we are measuring from one stock to another. This would be the flow of people from uninfected to infected population, or nitrogen from lake water to the algae population. Flows can also represent a source or sink of our measured quantity. A Source flow could represent immigration and births adding people, while a Sink flow would could represent people's deaths. Similarly a Source for nitrogen could represent runoff from farmland.

Iburns: /* Dynamical System Models */

2017-10-08T01:06:33Z

Dynamical System Models

← Older revision		Revision as of 01:06, 8 October 2017
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	===Goals of Developing Dynamical Systems Models===		===Goals of Developing Dynamical Systems Models===
	Dynamical Systems Models are used to describe when something you are measuring moves from one place to another, or transforms from one thing to something else. This may be modelling the flow of Carbon between various reservoirs, or it may be modeling the different cohorts in a population as they age. It can even represent the flow between sick and infected populations. The key point is that you have a measurable quantity being shuffled between categories without being lost in the transfer.		Dynamical Systems Models are used to describe when something you are measuring moves from one place to another, or transforms from one thing to something else. This may be modelling the flow of Carbon between various reservoirs, or it may be modeling the different cohorts in a population as they age. It can even represent the flow between sick and infected populations. The key point is that you have a measurable quantity being shuffled between categories without being lost in the transfer.

			===Dynamical Systems Models in NumerusMD===
			In NumerusMD we use the Stock and Flow objects. Stocks represent a pool of what we are measuring: infected population, nitrogen in lake water, and so on. Flows represent the movement of what we are measuring from one stock to another. This would be the flow of people from uninfected to infected population, or nitrogen from lake water to the algae population. Flows can also represent a source or sink of our measured quantity. A Source flow could represent immigration and births adding people, while a Sink flow would could represent people's deaths. Similarly a Source for nitrogen could represent runoff from farmland.

	==Spatial Models==		==Spatial Models==