### Aggregator

SC-IPM uses aggregators (eg,

`prod`

,

`sum`

)
to combine the results of subsidiary

Variables
(eg,

`assim_eff`

,

`conc`

,

`grazing_rate`

).

### Constraint

SC-IPM uses sets of constraints
(eg,

`always-together`

,

`atmost-one`

,

`exactly-one`

,

`necessary`

)
to control the inclusion of

Generic Processes
in a

Model Structure.

### Equation

SC-IPM uses algebraic and differential equations
to specify mathematical relationships
among

Generic Entities
and

Generic Processes.
See the

Equation page for details.

### Entity Instance

Each entity instance
(in the current

Instance Library)
provides SC-IPM with:

- the instance name (eg,
`aurelia`

, `nasutum`

)
- the instance type (eg,
`grazer`

, `producer`

)
- parameter types (eg,
`assim_eff`

, `attack_rate`

)
- variable bindings (eg,
`conc`

, `grazing_rate`

)

### Entity Role

Each

Generic Process may be used in
one or more entity roles (eg,

`G`

,

`P`

), each of which has
one or more

Entity Types (eg,

`grazer`

,

`producer`

).

### Entity Type

Each

Generic Entity and

Entity Instance
has an entity type (eg,

`grazer`

,

`producer`

).

### Fitness Score

Parameter Estimation generates a fitness score
for each

Model.
This is used to sort and filter the list of models that SC-IPM displays.

### Generic Entity

SC-IPM uses generic entities (eg,

Grazer,

Producer) to describe and define
the general nature of entities in the resulting models.
Each generic entity has an

Entity Types
(eg,

`grazer`

,

`producer`

).

### Generic Library

The generic library (eg,

`pplib`

) tells SC-IPM what kinds of

Generic Entities and

Generic Processes are available
and what

Constraints limit their inclusion
in a

Model Structure.

### Generic Process

SC-IPM uses generic processes (eg,

Grazing Predation,

Logistic Growth) to describe and define
the general nature of processes in the resulting models.

### Induction

IPM uses induction to assist in the creation and evaluation
of

Models and

Model Specifications.

Inductive reasoning, also known as induction or informally "bottom-up" logic,
is a kind of reasoning that constructs or evaluates general propositions
that are derived from specific examples.
-- Inductive reasoning (WP)

### Inductive Process Modeling

Inductive Process Modeling (IPM) assists in the creation of

Models
that are both descriptive and explanatory.
Using assorted techniques
(eg,

Induction,

Parameter_Estimation),
it helps the modeler to generate, evaluate, and modify models.

SC-IPM, in particular,
creates candidate

Model Structures,
based on

Model Specifications
(

Constraints,

Entity Instances,

Generic Entities, and

Generic Processes).
See the

Introduction page
for a summary of IPM's motivation and approach.

### Instance Library

The instance library tells SC-IPM which

Generic Library,

Parameters, and

Variables to use,
what

Entity Instances
(eg,

`aurelia`

,

`nasutum`

) to create, etc.

### Model

SC-IPM generates and evaluates mathematical models,
based on

Model Specifications
and a set of

Training Data.

### Model Specification

SC-IPM's model specifications consist of

Constraints,

Generic Entities,

Generic Processes,

Parameters, and

Variables.

### Model Structure

SC-IPM generates sets of candidate Model Structures,
based on a

Model Specification.

### Parameter

Generic Entities and

Generic Processes
may have associated Parameters (ie, parametric constants).
Each Parameter (eg,

`attack_rate`

,

`assim_eff`

,

`gmax`

)
is specified with

`lower-bound`

and

`upper-bound`

values.
This limits the range of numeric values considered
during

Parameter Estimation.

### Parameter Estimation

SC-IPM performs Parameter Estimation on validated

Model Structures,
fitting their

Parameters to the training data.

### Satisfiability

Each candidate

Model Structure
must pass a

Boolean satisfiability test
to ensure that it has a valid structure
and meets all specified

Constraints.

### Training Data

Each

Instance_Library (eg,

`pp-instances`

)
specifies a list of input data files (eg,

`pp-sim`

).
This data is used to "train" (and sometimes test)
the

Parameter Estimation.

### Variable

Generic Entities and

Generic Processes
may have associated Variables.
Each Variable is specified by an

Aggregator (eg,

`prod`

,

`sum`

) or an

Equation.