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 and simultaneously** 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.
** the model mimics simultaneous updating by first updating each node in a network and then beginning it's next cycle.
This particular example models a coherence network with the influence of affect represented as star nodes.
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.
Thagard (2000) offers the following principles to be considered in the design of PDP models of utility and which principles may be applied to !ARU:
"Principle L1: Symmetry Coherence and incoherence are semmetrical relations: if factor (action or goal) F1, coheres with factor F2, then F2 coheres with F1.
Principle L2: Facilitation Consisder actions Ai, . . . , An that together facilitate the accomplishment of goal G. Then
(a) each Ai coheres with G,
(b) each Ai coheres with each other Ai, and
(c) the greater the number of actions required, the less the coherence among the actions and goals.[we may imagine this to be a way to interpert work ]
Principle L3: Incompatibility
(a) If two factors cannot bother be performed or achieved, then they are strongly incoherent.
(b) If two factorss are difficult to perform or achieve together, then they are weakly incoherent.
Principle L4: Goal priority Some goals are desirable for intrinsic or other noncoherence reasons.
Principle L5: Judgment Facilitation and competition relations can depend on coherence with judgments about the acceptability of factual beliefs.
Principle L6: Decision Decisions are made on the basis of an assessment of the overall coherence of a set of actions and goals (p. 128)."
Actions like hypotheses are evaluated with respect to their coherence with each other and with goals. In addition goals get a degreee of priority since they will connect directly with specials or else Vspecials via a valence node.
Click the button labeled Affective Bias
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.
Click the button at the top right labeled display output to see display of the current status of each node.
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.
Click random net.
A random network is now created with labels indicating the theories and node numbers.
You can then use other contorols to modify and run the network created.
Because network links are created at random, you may create networks that do not always conform to the principles guiding !ARU. You can bring them into conformance using the lision-link button, for example, if a link is created between an orange node and a theory node.
Using controls along the top of the interface,
Click valence off
click balance weights
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
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, identify 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.
Click the control labeled "leison links"
Using your mouse point to the midpoint of the link to be deleted, click on each link to delete.
Click the "leison links" control again after having deleted all nodes you selected.