ACT-R 6.0 (Cognitive Science Prosem) Wayne D. Gray Rensselaer Polytechnic Institute

1. ACT-R 6.0 (Cognitive Science Prosem) Wayne D. Gray Rensselaer Polytechnic Institute CogWorks Laboratory grayw@rpi.edu Mike Schoelles Rensselaer Polytechnic Institute CogWorks Laboratory schoem@rpi.edu

2. Tutorial Overview • Cognitive Architecture/Modeling Overview • ACT-R Theory - Symbolic level • Addition,counting and letter models • ACT-R Theory Sub-symbolic level • Sternberg and Building Sticks models • Production Compilation

3. What is a Cognitive Architecture? • Infrastructure for an intelligent system • Cognitive functions that are constant over time and across different task domains • Analogous to a building, car, or computer

4. Unified Theories of Cognition • Account of intelligent behavior at the system-level • Newell’s claim • “You can’t play 20 questions with nature and win”

5. Integrated Cognitive Architecture • Cognition does not function in isolation • Interaction with perception, motor, auditory, etc. systems • Embodied cognition • Represents a shift from • “mind as an abstract information processing system” • Perceptual and motor are merely input and output systems • Must consider the role of the environment • Other body processes • Effects of caffeine, stress and other moderators

6. Motivations for a Cognitive Architecture * 1. Philosophy: Provide a unified understanding of the mind. 2. Psychology: Account for experimental data. 3. Education: Provide cognitive models for intelligent tutoring systems and other learning environments. 4. Human Computer Interaction: Evaluate artifacts and help in their design. 5. Computer Generated Forces: Provide cognitive agents to inhabit training environments and games. 6. Neuroscience: Provide a framework for interpreting data from brain imaging. 7. All of the above

7. Requirements for Cognitive Architectures* 1.Integration, not just of different aspects of higher level cognition but of cognition, perception, and action. 2. Systems that run in real time. 3. Robust behavior in the face of error, the unexpected, and the unknown. 4. Parameter-free predictions of behavior. 5. Learning.

8. Newell’s Time Scale of Human Activity (amended)

9. Taxonomy Computational Cognitive Models Connectionist Symbolic Home grown -- one-off code Cognitive Architectures Other AI other Production System Hybrid Symbolic only ACT-R 6.0 SOAR EPIC

11. History of the ACT-framework* Predecessor HAM (Anderson & Bower 1973) Theory versions ACT-E (Anderson, 1976) ACT* (Anderson, 1978) ACT-R (Anderson, 1993) ACT-R 4.0 (Anderson & Lebiere, 1998) ACT-R 5.0 (Anderson & Lebiere, 2001) Implementations GRAPES (Sauers & Farrell, 1982) PUPS (Anderson & Thompson, 1989) ACT-R 2.0 (Lebiere & Kushmerick, 1993) ACT-R 3.0 (Lebiere, 1995) ACT-R 4.0 (Lebiere, 1998) ACT-R/PM (Byrne, 1998) ACT-R 5.0 (Lebiere, 2001) Windows Environment (Bothell, 2001) Macintosh Environment (Fincham, 2001) ACT-R 6.0 (Bothell, 2004??)

12. Other Cognitive Architectures • Soar • Production rule system • Organized in terms of operators associated with problem spaces • Goal oriented • Sub-goaling • Learning mechanism - Chunking • EPIC -- Executive Processes in Cognition • Parallel firing of production rules (in principle) • Well developed visual and motor system • Emphasis on executive processes

13. MetaIssues • The divide between high-level architectures and low-level (primarily connectionist ones) is mainly a levels issue • Modeling in high-level architectures reflects a concern with the task structure of behavior and can be considered a form of task analysis

14. MetaIssues • The problems tackled by the two sets of approaches tends to reflect this difference • From this perspective ACT-R is a major success in “re-use” -- low level parameters are reused in most ACT-R models. • The higher level production rules differ in part because they reflect the task analysis for the different tasks being modeled

15. MetaIssues • From this perspective the focus on reusability should focus on • Low-level productions that control the interleaving of cognitive, perceptual, and action at the 1/3 sec level of analysis • Not on • High-level productions that implement task-specific executive control

16. MetaIssues • Low-Level Productions Implement Interactive Routines

17. MetaIssues • Interactive Routines • Neurocognitive evidence increasing stresses the modular nature of human cognition • But -- these modules are constrained by their need to work together to survive in the world • Interactive routines can be viewed as the basic level elements of embodied cognition • Provide constraints on the input/output functions for perception, attention, memory, and motor systems • Notion is that the use of cognitive, perceptual, and motor resources is optimized via the selection of one set of interactive routines over another

18. ACT-R Overview • Modules (buffers) • Knowledge Representation • Symbolic/Sub-symbolic • Performance/Learning

19. ACT-R Applications 559 Papers Listed on http://act-r.psy.cmu.edu/publications/index.php In the following areas as of 2006-01-24

20. Interactive Session • Load and run Addition model

21. Addition model exercise In this exercise you will load a simple model and run it to see how a model runs. You will also get some experience with the interface. 1. Open model Click on the "Open Model" button on the Environment Control Pane, and select the Addition model. This will open up the model so that you can see it and its parts. You should be able to see the working memory elements in the model (window "Chunk"), the productions (Production window). There are three further windows, Chunk Type, Command, and Miscellaneous, that we will cover later. You should briefly examine the chunk and production contents. You may note that there about 11 pieces of working memory, and just 4 rules in this system.

22. 2. Run the model You can run the model using the Lisp command line, but we will use the environment because it provides a recognition-based interface rather than a recall-based interface. You should first click on "Reset"; this will reset the model and make it ready to run. You can do this to a model that has run as well, or has been stopped in the middle of a run. You can run the model by clicking on the "Run" button. A trace of the model will appear in the (Lisp) "Listener" window. You can see how the order that rules are selected and fired, as well as when chunks are retrieved from memory by the rules.

23. 3. Inspect the model Click on "Declarative viewer" in the Control Pane to bring up an inspector window for the declarative memory elements. If you scroll, you can find the chunks a-j and second-goal. Pay most attention to their structure, and note that they have several parameters. These parameters are used to compute how fast they are used and if they can be retrieved. With learning and use, the activation, for example, goes up. These are covered later in this tutorial. The Procedural viewer provides a view onto the rules.

24. End of First Tuesday • Homework • Anderson, J. R., Bothell, D., Byrne, M. D., Douglas, S., Lebiere, C., & Quin, Y. (2004). An integrated theory of the mind. Psychological Review, 111(4), 1036-1060. • Change addition model to subtraction model

25. ACT-R 6.0 Current Goal Declarative Memory Modify Retrieve Check Test Pattern Matching And Production Selection Identify Object Check State Schedule Action Move Attention Motor Modules Perceptual Modules Environment ACT-R 6.0 Architecture

26. ACT-R 6.0 Mapping to the Brain* Intentional Module (not identified) Declarative Module (Temporal/Hippocampus) Goal Buffer (DLPFC) Retrieval Buffer (VLPFC) Matching (Striatum) Productions (Basal Ganglia) Selection (Pallidum) Execution (Thalamus) Visual Buffer (Parietal) Manual Buffer (Motor) Manual Module (Motor/Cerebellum) Visual Module (Occipital/etc) Environment

27. ACT-R: Assumption Space*

28. ACT-R: Knowledge Representation*  goal buffer  visual buffer  retrieval buffer

29. Declarative Memory Syntax Chunk type : ((chunk-type type-name slot-name1 …(slot-namek init-val)..slot-namen) (chunk-type count-order first second) (chunk-type add arg1 arg2 sum count) Chunk Instantiation: (add-dm (chunk-name isa type-name slot-name slot-value) …) (add-dm (a ISA count-order first 0 second 1) (b ISA count-order first 1 second 2) (second-goal ISA add arg1 5 arg2 2) ) ;;sum and count are nil

30. Declarative Memory • Chunks that are added explicitly • Add-dm • Chunks merge into DM from buffers • All buffers’ chunks go to DM when cleared • Mergings are the references for BLL • Not the LHS usage as in ACT-R 5 • Because buffers hold copies, DM chunks can’t be changed from within a production • Previously it was a recommendation

31. ( FACT3+4 ADDITION-FACT isa ADDEND1 THREE ADDEND2 FOUR ) SUM SEVEN Addition Fact Example (Chunk-type addition-fact addend1 addend2 sum)

32. Addition Example (CLEAR-ALL) (DEFINE-MODEL addition) (CHUNK-TYPE addition-fact addend1 addend2 sum) (CHUNK-TYPE integer value) (ADD-DM (fact3+4 isa addition-fact addend1 three addend2 four sum seven) (three isa integer value 3) (four isa integer value 4) (seven isa integer value 7)

33. Addition Fact Example ADDITION-FACT 3 7 VALUE isa VALUE ADDEND1 SUM THREE SEVEN FACT3+4 ADDEND2 4 isa isa FOUR VALUE isa INTEGER

34. A Production is* 1. The greatest idea in cognitive science. 2. The least appreciated construct in cognitive science. 3. A 50 millisecond step of cognition. 4. The source of the serial bottleneck in otherwise parallel system. 5. A condition-action data structure with “variables”. 6. A formal specification of the flow of information from cortex to basal ganglia and back again.

35. Productions* • modularity • abstraction • goal/buffer factoring • conditional asymmetry Key Properties Structure of productions ( p name Specification of Buffer Tests condition part delimiter ==> Specification of Buffer Transformations action part )

36. Productions LHS • Only four possible conditions available =buffer> • Test the chunk in the buffer just like in 5 !eval! or !safe-eval! !bind! or !safe-bind! • Same as in ACT-R 5 • Safe- versions accepted by production compilation ?buffer> • Query the buffer or its module • Come back to queries later

37. Possible RHS actions • =buffer> • -buffer> • +buffer> • !eval! and !safe-eval! • !bind! and !safe-bind! • !output! • !stop!

38. RHS actions • =buffer> • !eval! and !safe-eval! • !bind! and !safe-bind! • !output! • All the same as in ACT-R 5 • The safe- versions do not inhibit the production compilation mechanism • !stop! • Not actually new, but does work now • Generates a break event in the scheduler • Terminates the current “run” command

39. RHS +buffer> +buffer> isa chunk-type {{modifier} [slot | request parameter] value}* or +buffer> chunk-reference • Sends a request to the module • Always clears the buffer implicitly • Essentially the same as ACT-R 5

40. Buffer queries • Replaces the *-state buffers • Syntax ?buffer> { {-} query value}+ • Either true or false • No bindings • Must all be true for production to match • Examples ?retrieval> ?visual> state busy - state error buffer empty buffer =check

41. Queries continued • Every buffer/module must respond to • State • Values: busy, free, or error • Buffer • Values: full, empty, requested or unrequested • Others can be added by a module writer • Modality for the current PM modules for example

42. Production Syntax (P initialize-addition =goal> ISA add arg1 =num1 arg2 =num2 sum nil ==> =goal> sum =num1 count 0 +retrieval> isa count-order first =num1 ?retrieval> state free ) (P increment-sum =goal> ISA add sum =sum count =count =retrieval> ISA count-order first =sum second =newsum ==> =goal> sum =newsum +retrieval> isa count-order first =count )

43. (p got-number =goal> isa make-a-call who =person =retrieval> isa phone-number who =person where =office ph-num =num ==> !output! (The phone number for =person is =num) +goal> isa dial-number who =person ph-num =num current-digit 1 ) (p dial-a-digit =goal> isa dial-number ph-num =num current-digit =digit state nil ==> !bind! =d (get-digit =digit =num) +visual-location> isa visual-location value =d =goal> state dialing )

44. (P increment =goal> ISA count-from start =num1 - end =num1 step counting =retrieval> ISA count-order first =num1 second =num2 ==> =goal> start =num2 +retrieval> ISA count-order first =num2 !output! (=num1) ) (p read-choose =goal> isa read-letters state verify-choose =visual> isa text value "choose" ==> =goal> state find-letter )

45. (P rotate-counter-clockwise =goal> ISA translate&rotate step counter-clockwise reference-y =y axis =axis form =form !bind! =y1 (+ =y 15)) =retrieval> ISA point-i > screen-y =y1 ;;no longer can do (!eval! (+ =y 15)) ==> !eval! (rotate-counter-clockwise =form =axis) ) (P get-direction =goal> ISA make-report step find-point =retrieval> ISA point-i screen-x =x screen-y =y ==> =goal> step find-direction !bind! =x1 (+ =x 15) +retrieval> ISA direction < screen-x =x1 ;;;no longer (!eval! (+ =x 15)) )

46. Interactive Session • Load and run Counting model

47. Count model This model works much like the previous model, but prints out its count. 1. Open the model Either quit and restart your Lisp, or else click on "Close Model". Open the Count model by clicking on "Open Model" and then selecting the Count model. Run the model to see its trace, and examine its rules and chunks. 2. Using the Stepper Click on "Stepper", and a stepper window should appear. Reset the model, and then click on the run button. This starts the stepper. You can now step through the model by clicking on the "Step" button on the Stepper. As you step through the model, you should be able to see most of the mechanisms in ACT-R now, the productions, how they are matched, the chunks, and how they are retrieved, and the buffers (click on Buffer Viewer to see the buffers and their contents).

48. 3. Checking on a rule that does not fire. • After you have run the model a few steps, click on the Procedural Viewer. Select a rule in the dialogue box, and see why it does not fire. • 4. Edit the model • Look at the model and consider how to have it count backwards. • You can change the production rules in the Production window. After you make changes, save the model (it will automatically increment). Close the model and reopen it to try your new model.

49. The Modules(reprise) • Cognition • Memory • Vision • Motor • Audition • Speech

50. ACT-R 6.0 Buffers* 1. Goal Buffer (=goal, +goal) -represents where one is in the task -preserves information across production cycles 2. Retrieval Buffer (=retrieval, +retrieval) -holds information retrieval from declarative memory -seat of activation computations 3. Visual Buffers -location (=visual-location, +visual-location) -visual objects (=visual, +visual) -attention switch corresponds to buffer transformation 4. Auditory Buffers (=aural, +aural) -analogous to visual 5. Manual Buffers (=manual, +manual) -elaborate theory of manual movement include feature preparation, Fitts law, and device properties 6. Vocal Buffers (=vocal, +vocal) -analogous to manual buffers but less well developed