view/download model file: ARU_Explanatory_Breath_B.nlogo
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The theory of explanatory coherence can be summarised in the following principles (Thagard 1992. Conceptual revolutions. Princeton, NJ: Princeton University Press, 2000. Coherence in thought and action. Cambridge, MA: MIT Press.)
Principle E1. Symmetry. Explanatory coherence is a symeteric relation,
unlike, say, conditional probability. That is, two propositions p and q cohere with each other equally.
Principle E2. Explanation. (a) A hypothesis coheres with what it explains, which can either be evidence or another hypothesis; (b" hypothesis that together explain some other propositon cohere with each other' and (cc) the more hypothesies it takes to explain something, the lower the degree of coherence.
Principle E2. Analogy. Similar hypotheses that explain similar pieces of evidence cohere.
Principle E4. Data priority. Propositions that describe the results of observations have a degree of acceptability on their own.
Principle E5. Contradiction. Contradictory propositions are incoherent with each other.
Principle E6.Competition. If P and Q both explain a propostion, and if P and Q are not explanatorily connected, the P and Q are incoherent with eachother. (P and Q are explanatorily connected if one explains the other or if thgether they explain something.)
Principle E7. Acceptance. The acceptability of a proposition in a system of propositions depends on its coherence with them.
This model provides the user with the ability to rationally assess competing ideas on the basis of coherence using a connectionist formula to update the activation of interconnected nodes. The network is also a (PDP) Parallel Distributive Processing Model in the sense that each node acts independently to update its activation with information about only those nodes with which it is immediately connected.
As activation of a node increases, the node size increases. As activation decreases, the node size decreases. Below activation 0.0 the node changes from a circle to a triangle representing rejection. Some models may have nodes that include a valence in addition to an activation. Changes in valence are indicated by color changes of the nodes.
With the exception of orange special nodes set at 1, the default activation of a node is 0.01. Changes of activation and valences is achieved via links between the nodes. Positive links, colored green, are created with a default weight of 0.04 while negative links, colored red, have a default weight of -0.06. The activation and valence of unconnected nodes will decay at a rate of 0.05 per cycle.
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ensure that the switch at top left labeled "enter-file?" is set to off,
click the button labeled "valence off"
click the button near the top right labeled "balance weights" then
click on "the button labeled "go".
As activation of a node increases, the node size increases. As activation decreases, the node size decreases. Below activation 0.0 the node changes from a circle to a triangle representing rejection. If "valence off" is not selected, color changes will represent the flow of valence through the network.
Since both theories have equal explanatory breath but unequal simplicity, the network accepts the simpler explanation of therapy.
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Controls for the creation of random networks are located at the bottom of the interface.
Drag the Number-of-theories slider with your mouse to set the desired number of theories.
Use the Number-of-nodes slider to set the total number of nodes for the network to create.
Use the Number-of-links slider to set the maximum number of links from each node.
Set the Affect? switch to off.
Click random net.
A random network is now created with labels indicating the theories and node numbers.
You can then use other contorols run the network created. Using controls along the top of the interface,
Click valence off
click balance weights
click go
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Set the "enter-file?" switch to "on" using your mouse.
Click the "read file" button. A box appears from which you may choose a .txt script.
Inspect the network that is created.
if there are no links connecting the orange pentagon node proceed as follows:
click the button labeled "valence off"
click the button near the top right labeled "balance weights" then
click on the button labeled "go";
if the orange pentagon node is linked to any other node,
click the button near the top right labeled "balance weights" then
click on the button labeled "go".
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Set the "number-of-theories" slider to the number of theories to be assessed.
Set the "number-of-nodes" slider to 0
Set the "number-of-links" slider to 0
Set the Affect? switch to on.
Click "RandomNet"
Controls for creating and connecting individual nodes are in a column along the left.
Four types of nodes plus connecting links can be created.
Click the "AddObservation" button. A user input box appears.
Type a brief description of an observation to be evaluated., e. g., It blows my mind.
Click the "AddHypothesis" button. A user input box appears.
Type a brief description of a concept to be evaluated., e. g., Because the wind is high.
If you wish to model the influence of values and emotions
Click the "+V" button to create a special positively Valenced node.
Click the "-V" button to create a special negatively Valenced node.
Click the control labeled "leison nodes"
Using your mouse, click on each node to delete. All links to the node will be deleted as well.
Click the "leison nodes" control again after having deleted all nodes you selected.
Several types of nodes may be created with default settings and user interpretations. NOTE: Any nodes that are added by the user can only operate correctly if the network is reset to it's initial conditions before making additions and "Accounts" of new relationships among nodes must be done only after all new nodes have been added. To run your newly revised network, click reset, then balance weights, then go.
Look in the left hand column of buttons.
Click the button labeled "AddObervation" to add nodes representing the interface between the world and how our senses interpret observation. A user input box appears allowing you to enter a brief descriptive label of the observation to be interpreted, e.g. "the wind turns me on". ARU will then create a new node of activation 0.01 with your discriptive label and identify the number of the node, the fact that it is to be regarded as evidence, and link it to a special node. At a later stage in developing your network you can use the mouse to link your new node to others.
Click the button labeled "AddHypothesis" to add nodes representing concepts that may account for some bits of evidence. A user input box appears allowing you to enter a brief descriptive label of your hypothesis, e.g., "Because the wind is high" Another box appears allowing you to assign your hypothesis to a collection of nodes representing hypotheses that give a collective name, e.g., "T1". ARU will then create a new node of activation 0.01 with your descriptive label and idenditvy the number of the node, and tag it as a hypothesis. At a later stage in developing your network you can use the mouse to link your new node to nodes representing supporting evidence and other concepts withwhich it may cohere or in-cohere.
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Create scripts using any simple .txt editor.
Comments are of the form " ; bla bla . .bla" 0 0
Instructions are provided to the model as a triple separated by spaces
followed by a line return, e. g., 1 1 1
the first digit may be from 0 to 10 and provides the instruction.
the second and third digits name the nodes involved in the instruction
and/or specify the value of an instruction.
The first instruction beginning with 0 sets up the network and
the second digit, 1, creates two special nodes clamped at the activation 1.
the third digit provides the number of nodes to be created.
e.g., 0 1 15 creates a network with 16 nodes the first two of which are special.
Note: The first special node, node 0, is clamped at activation 1 and is to be linked to only those nodes which are created as valenced nodes for the purpose of modeling the influence of affect. The second special node, node 1, is also kept at activation 1 and is to be linked only to those nodes representing observations. All other nodes have a default initial activation of 0.01 and valence of 0.01. Activation and valence of nodes will decay unless their values are influenced by their connections to other nodes.
To provide interpretive labels for the nodes created, provide an instruction beginning
the first digit, 5, followed by
the second digit which is the number of the node to be labeled, followed by
the third entry, which is the label in quotes,
e.g., 5 4 "Nice Hypothesis"
To set the number of theories to be entertained, provide an instruction beginning
the first digit, 8, followed by
the second digit, 0, followed by
the third digit, which digit is the number of theories entertained.
e.g., 8 0 3 says that there will be three theories in competition.
Note: The model uses the number of theories together with information about the number and relationships of hypotheses to account for judgments of simplicity and explanatory breath.
To connect nodes that cohere provide an instruction beginning
the first digit, 1, followed by
the second digit, which is the number of a node, followed by
the third digit, which is the number of the node to which it is to be connected.
e.g., 1 4 5 connects nodes four and five with a default positive weight set at 0.04
Note: also create positive links between all nodes representing observations and the special node 1.
To connect nodes that in-cohere provide an instruction beginning
the first digit, 2, followed by the number of each node to be connected.
e.g., 2 4 5 connects nodes four and five with a default negative weight set at -0.06
To connect nodes that explicitly contradict provide an instruction beginning
the first digit, 6, followed by the number of each node to be connected
e.g., 6 10 11 connects nodes ten and eleven with a weight of - 1.0
In addition to coherence and incoherence the model will require information about relatationships among hypotheses
the first digit, 7 , marks the node in
the second digit as explained-by (This node may be evidence or background)
the third digit which is the node in need of explanation
e.g., 7 5 2 says that some data 2 is explained by hypothesis 5
To identify a node as belonging to a theory, provide an instruction beginning
the first digit, 10, followed by
the second digit, which names the node to be identified as belonging to
the third entry, which will be alpha numeric and in quotes specifying a theory name.
e.g., 10 3 "T1" says that some hypothesis 3 belongs to the theory named T1.
Note: the model does not explicitly provide for the possibility that two theories may share hypotheses, although such a conclusion may be drawn from the results of a settled network.
The model may create Valenced nodes to provide for the influence of values and emotion.
the first digit 3 followed by
the second digit, which specifies a node used to deliver positive valence, followed by
the third digit, which specifies what value at which to initialize the valence.
e.g., 3 9 0.05 says that node 9 will have an initial valence of 0.05
Note: a valenced node must have a positive link to the vspcial node work.
Create Negatively Valenced nodes to model the influence of negative values and emotion.
the first digit, 4, followed by
the second digit, which specifies a node used to deliver positive valence, followed by
the third digit, which specifies the value at which to initialize the valence.
e.g., 4 10 0.05 says that node 10 will have an initial valence of -0.05
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"; *==== dynamic connectionist representation ====* " 0 0
"; describes the simplest account of competition between " 0 0
"; psychotherapy and social rehabilitation " 0 0
0 1 7
" ; we hypothesize that " 0 0
" ; actions of the body, e.g. production of cortisol, " 0 0
" ; adrenalin, etc. associated with affect, influence " 0 0
" ; the activation of neurons " 0 0
" ; But, we wish to first model coherence based reasoning independent " 0 0
" ; of emotional influences. So, there are no pathways by way of which " 0 0
" ; valence may flow in this example. " 0 0
5 0 "AFFECTIVE influence"
10 0 ""
" ; two theories are to be entertained " 0 0
8 0 2
" ; we hypothesize that " 0 0
" ; if there is an independent world, that world will " 0 0
" ; influence the activation of neurons " 0 0
" ; if there is no independent world, a story needs to be " 0 0
" ; told about what source provides this degree of input " 0 0
" ; perhaps it is the influence of god or angels " 0 0
5 1 "WORLD influence"
10 1 ""
" ; the model is silent on the ontological status of perceptions " 0 0
" ; materialist may interpret in a topic neutral way " 0 0
" ; dualist and epiphenomenalist may see qualia here " 0 0
" ; in any case this collection of nodes is excited when instances of " 0 0
" ; their corresponding object types are present " 0 0
" ; This is the the data, evidence, or observation to be accounted for " 0 0
5 2 "Exemplary THERAPY"
10 2 ""
" ; ============= Hypotheses of initil Theory ================== " 0 0
" ; These nodes represent elements of Theory one " 0 0
5 3 "ID"
10 3 "T1"
5 4 "EGO"
10 4 "T1"
5 5 "SUPER-EGO"
10 5 "T1"
5 6 "TRANSFERENCE"
10 6 "T1"
5 7 "COUNTER-TRANSFERENCE"
10 7 "T1"
" ; ============== coherence relations " 0 0
" ; co-hypotheses of a theory share the weight of their relevance " 0 0
" ; nodes 3, 4, and 5 together explain Evidence node 2 " 0 0
7 2 3
7 2 4
7 2 5
" ; nodes 6 and 7 are auxiliary hypotheses that help account for node 2 " 0 0
7 2 6
7 2 7
" ; nodes 6, and 7 together explain only on the assumption of 3, 4, 5 " 0 0
7 6 3
7 6 4
7 6 5
7 7 3
7 7 4
7 7 5
" ; =========== positive links between nodes of initial theory " 0 0
1 1 2
1 2 3
1 2 4
1 2 5
1 2 6
1 2 7
1 3 4
1 3 5
1 3 6
1 3 7
1 4 5
1 4 6
1 4 7
1 5 6
1 5 7
1 6 7
" ; ========== negative links between nodes of competing hypotheses " 0 0
2 8 3
2 8 4
2 8 5
2 8 6
2 8 7
" ; ============ Alternative Hypotheses =========== " 0 0
5 8 "ENVIRONMENT ADJUSTMENTS"
10 8 "T2"
" ; ============== coherence relations " 0 0
" ; nodes 8 explains Evidence node 2 " 0 0
7 2 8
" ; =========== positive links between nodes of alternative theory " 0 0
1 2 8