代写 R lisp graph software theory Dynamic Visualization of ACT-R Declarative Memory Structure

Dynamic Visualization of ACT-R Declarative Memory Structure
Andrea Heiberg2 (Andrea.Heiberg@mesa.afmc.af.mil)
Jack Harris1 (Jack.Harris@mesa.afmc.af.mil)
Jerry T. Ball1 (Jerry.Ball@mesa.afmc.af.mil)
1Air Force Research Laboratory / 2L-3 Communications at Air Force Research Laboratory 6030 S. Kent St.
Mesa, AZ 85212 USA
Introduction
We propose an automated technique for visualizing changes to declarative memory (DM) in the ACT-R 6 cognitive architecture (Anderson et al., 2004; Anderson & Lebiere, 1998). In this technique, DM chunks and the relationships between chunks are displayed graphically in a labeled tree diagram. A series of diagrams, automatically generated during a model run, allows the modeler to easily visualize how DM changes over time. The technique is potentially useful for any ACT-R model with a complex DM structure.
Labeled Tree Diagrams
Labeled tree diagrams are commonly used in theoretical linguistics (e.g., Radford 1988) to represent constituent structure. The structure of ¡°I increased the airspeed¡± may be represented as in Figure 1. Top-level SENTENCE contains constituents NOUN-PHRASE and VERB-PHRASE; VERB-PHRASE contains VERB (¡°increased¡±) and NOUN-PHRASE (¡°the airspeed¡±), and so on. Figure 1 was generated from labeled bracket notation with a third-party software tool, phpSyntaxTree (Eisenbach & Eisenbach, 2006).
Figure 1 Labeled Tree Diagram
Similar diagrams have long been used for exposition of cognitive models (e.g., Anderson, 1983; Anderson, Budiu, & Reder, 2001).
Declarative Memory Structure Visualization
The automated, dynamic visualization technique is being used in the ACT-R implementation of the Double R model of language comprehension (Ball, 2007; Ball, Heiberg, & Silber, 2007). Figure 2 shows a graphical representation of the final DM structure for ¡°I increased the airspeed¡±. The nodes of the tree are the names of chunks and slots. The tree structure captures the relationships between chunks. For example, chunk PRED-TRANS-VERB (transitive verb
predicate) has three constituent slots, SUBJ (subject), HEAD, and OBJ (object); OBJ contains an OBJ-REFER- EXPR (object referring expression) chunk, etc.
Figure 2 Double R Model DM Structure
The diagrams are also used to visualize changes to DM during the model run. Figure 3 shows a DM snapshot after processing ¡°I¡±; Figure 4, ¡°increased¡±; Figure 5, ¡°the¡±; and Figure 2, the final structure after processing ¡°airspeed¡±.
For the development of the large-scale Double R model, the technique has proven to be greatly more efficient than examining DM by hand. Creating a series of representations takes seconds, as opposed to the minutes required to draw a single diagram by hand.
Figure 3 DM Snapshot after Processing ¡°I¡±
Figure 4 DM Snapshot after Processing ¡°increased¡±

Figure 5 DM Snapshot after Processing ¡°the¡±
The technique may also be applied to non-linguistic mod- els, to help visualize complex DM structures. An example from the ACT-R 6 tutorial (http://act-r.psy.cmu.edu/actr6) is the Siegler child addition (Siegler & Shrager, 1984) model. The chunks for that model include:
(two isa number value 2 name “two”)
(three isa number value 3 name “three”)
(five isa number value 5 name “five”)
(f23 isa plus-fact addend1 two addend2 three sum five)
Figure 6 shows a graphical representation of chunk f23:
Figure 6 Siegler Model DM Structure Implementation
During a model run, snapshots of DM are created by invoking image generation from ACT-R production rules. DM is traversed from a starting chunk; slots and chunks are recursively examined to produce a labeled bracket representation, which is then input to an image generator (phpSyntaxTree) that is integrated with the system. The code is written in Lisp; ACT-R 6 functions are used to traverse DM. The implementation is generic, and may be used with any ACT-R 6 model.
A DM chunk may ultimately refer to itself. To avoid infinite processing, traversal stops at any previously visited chunk. For example, in the communication model (Matessa, 1999; Matessa & Anderson, 2000) shown in Figure 7, chunk C5 appears at the top of the tree and in the BELOW slot of chunk C6. However, C5 is expanded only once.
Figure 7 Communication Model DM Structure Summary
The automated, dynamic visualization technique proposed here may be used to help understand the DM structure of an ACT-R model. Relationships between chunks are displayed graphically in a labeled tree diagram. A series of diagrams is automatically created during a model run to show how DM changes over time. The technique has proven to be particularly useful for the development and exposition of a large-scale model. The implementation of the technique is general, and so may be used with any ACT-R 6 model. The clear view of DM provided by the technique helps make assumptions about a model explicit; it is hoped that this will help provide a better understanding of cognitive modeling.
Acknowledgments
This research is funded by the Warfighter Readiness Research Division of the Air Force Research Laboratory.
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