eCognition Model Components
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Transcript of eCognition Model Components
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eCognition Model Components
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2. eCognition Model Components 2
Model Components
• Variables and Constants
• Operators and Functions
• Links
• Logical States
• Messages
• Change Storage
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If this is part of a larger model, how is it controlled?What does the EQUALS mean?How many ways should we be able to use this piece of knowledge?
a + b = c
A Simple Example
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Instead of writing programs, turn the knowledge itself into a computing machine
Programmatic:if input(a) and input(b) then c = a+belse if input(a) and input(c) then b = c-aelse…
a + b = c
A new approach to knowledge
Structure
NYK - Not Yet Known
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Values flow through the structure in any direction.
The EQUALS operator allows for logical control.
a + b = c
Use the structure itself
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Information Coming the Other Way
Example: a + b = c
We have a range on one variable, producing a range on another.
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Is It Just Numbers
The structure can propagate a wide range of entities through its connections, and the operators can be operating on analytic or experiential information, and the structure can be changing itself - it is a lot more than just numbers.
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Variables and Constants
Every variable and constant has a logical state and may have a value - logical, numerical, string, list, object.
Every variable and constant is a linkable object - it can support unlimited connections.
Variables are addressable by a name which can have unlimited depth of context and multiple context -
Model.Animal.Mammal.Whale.MobyDick
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Operators & Functions
The distinction between the two in the network is blurred
• many functions are invertible - ABS(X) • many functions are actually pieces of network machinery - WHILE, GETPUT, SEQUENCE
Operators have a fixed orientation to their connections (the number of connections may be variable - the PLUS operator can function with up to 1024 connections).
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Operators & Functions
The network has operators that are not obvious in the text
• SPINE and LEVEL operators allow logical structuring of network text
• INDEX operator to represent an index into a list• structure to represent potential inferences
Some textual representations convert to simpler forms
• Minus is a Plus operator with different orientation• a + b + c is held in the network as one operator
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Links
Links connect operators and variables together.
They store the information produced by operators, allowing an operator to have many concurrent outputs.
Links provide for bi-directional flow of information.
Operators can add links to themselves for storage of states, or an operator’s only purpose can be to add links to other operators - LISTLINK.
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Logical States
Logical states range over
• Not Yet Known• Unknowable - Bayesian values or existence• Error• False• True
and control the phasing of operations
R unningN YK U KE D oesn’tExist
BayesianValues
Valid
Error
True
False
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Messages
Messages can be • simple singular values - True, 2.3, “Fred”• objects - Joe, MobyDick, Glock• lists - {1,2,3}• Bayesian values - UKE 0.7• signalling nonexistence of structure • alternative values using list transmission - 2..4, 3<->6• structure - a < b, IF X > Y THEN P < Q
There is no conceptual limit on the size of a message, as it is constructed out of the same elements that make up the network
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Self Modification
X = + ListLink =
B
CA%
D
A%ListLink
X = + ListLink A%
X = +
B
C
D
B=9
C=3X=5
D=-7
+
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Change Storage
All changes to the network can be stored in memory in a layered fashion for later retrieval.
This allows values to be changed or hypothetical structure to be generated, its operation observed, and then the scenario to be undone.
A change can be attempted, and if successful, its changes merged with a previous store level which is still tentative.
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Functions and Operators
• eCognition provides a comprehensive set of predefined operators and functions.
• The operators in the network represent the elemental or atomic level of analysis
• Each operator determines its own activity, so the network is micro-scheduling what it does.
• The user can add script operators, and user-defined functions.
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Handling Uncertainty
• eCognition is designed to handle uncertainty – it can reason using partial or fuzzy knowledge.
• Variables can hold tentative knowledge – alternative values (ranges for numbers) or distributions.
• Logical variables can support values between False and True (0 to 1 is used, with 0.5 representing Unknowable). These intermediate values can be overridden, but True and False cannot be overridden.
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How It Works
• Setting the value of a variable causes the new value to propagate in all directions through the network, until there are no new paths to propagate
• Ranges of numbers, alternative strings and lists are also propagated
• Some operators alter their local topology and then destroy themselves
• Spreading activation is also used - one operator forces another to become active, as the message is too complex to propagate
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Logical Control
• Everything has a logical state
• Every statement or equation lives in a logical “block”, or environment, and is controlled by a “head” variable
• A head variable can turn its block on, make it false or unknown, or make it go dark
• A head variable can be tested for truth (higher structures are invertible too)
• Logical control allows the user, and the model itself, to control which part of the structure is active