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An Introduction to the COGENT Modelling Environment 8 th International Conference on Cognitive Modelling July 26 th, 2007 Ann Arbor, Michigan, USA Presented.

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Presentation on theme: "An Introduction to the COGENT Modelling Environment 8 th International Conference on Cognitive Modelling July 26 th, 2007 Ann Arbor, Michigan, USA Presented."— Presentation transcript:

1 An Introduction to the COGENT Modelling Environment 8 th International Conference on Cognitive Modelling July 26 th, 2007 Ann Arbor, Michigan, USA Presented by: Rick Cooper Birkbeck, University of London

2 Tutorial Overview 14:00: Introductory talk COGENT: Overview and principal features 14:30: Hands-on session (part 1) The COGENT Modal Model Model 15:30: Break 15:45: Hands-on session (part 2) Exploring the Model Model 16:45: Closing talk Architectures; Hybrid models; COGENT V3; Questions

3 1: Introductory Talk 14: :30

4 COGENT: Principal Features A visual programming environment in which models are developed via box and arrow diagrams; A range of standard functional components; An expressive rule-based modelling language; Automated data visualisation tools; A powerful model testing environment; and Research programme management tools

5 Visual Programming in COGENT

6 Standard Functional Components A library of standard configurable components: Memory buffers Rule-based processes Simple connectionist networks Data input/output devices TCP/IP sockets for inter-process communication Inter-module communication links Components are wired-up and configured for different applications using COGENTs graphical model design editor

7 Buffers: Purpose and Properties Buffers store symbolic information A buffers contents may be queried or modified by other COGENT components A buffers behaviour is specified by its properties, which include: Capacity (unlimited or specified number of items) Behaviour on exceeding capacity Access (FIFO, LIFO, random) Decay (No decay, fixed, linear, random) Decay rate (numerical)

8 Rule-Based Modelling Language: I Processes may contain rules such as: IFoperator(Move, possible) is in Possible Operators evaluate_operator(Move, Value) THENdelete operator(Move, possible) from Possible Operators add operator(Move, value(Value)) to Possible Operators

9 Rule-Based Modelling Language: II COGENTs representation language is based on the Prolog programming language: IFoperator(Move, possible) is in Possible Operators evaluate_operator(Move, Value) THENdelete operator(Move, possible) from Possible Operators add operator(Move, value(Value)) to Possible Operators

10 Rule-Based Modelling Language: III

11 Data Visualisation Tools: Tables

12 Data Visualisation Tools: Graphs

13 Data Visualisation Tools: Pictures

14 The Model Development and Testing Environment Dynamically updated visualisation tools allow a models functioning to be examined while the model runs Inter-component communication may be traced A flexible scripting environment allows: models to be run over multiple blocks of trials; multiple subjects to be run over multiple blocks; automated variation of parameter in meta- experiments.

15 Research Programme Management

16 2: Hands-on Session 14: :30

17 The Tutorial Task: Free Recall On each trial, the subject is presented with a list of (for example) 25 words The subject is told to try to memorise the words After an interval, the subject must recall as many words as possible (e.g., Glanzer & Cunitz, 1966)

18 Free Recall: Empirical Findings

19 The Modal Model: The Top Level

20 Inside the Task Environment

21 Inside the Subject Model

22 Messages Processed by I/O Process

23 Building the Short Term Store: I

24 Building the Short Term Store: II

25 Building the Short Term Store: III The rule to transfer words to STS:

26 Building the Short Term Store: IV

27 Building the Short Term Store: V The rule to recall from STS:

28 Building the Short Term Store: VI

29 Building the Short Term Store: VII Run more trials. What happens to the curve? Change the On Excess property of STS. What happens to the shape of the graph when you run a few trials? Watch the Messages view of Input/Output. What happens there now when you run (or single-step) through a trial?

30 Adding the Long Term Store: I The Modal Model also includes: a long term store (LTS); a rehearsal process to transfer information from STS to LTS; and the possibility to recall information from either STS or LTS

31 Adding the Long Term Store: II

32 Adding the Long Term Store: III The rehearsal rule:

33 Adding the Long Term Store: IV Recalling from either STS or LTS:

34 Adding the Long Term Store: V

35 Adding the Long Term Store: VI What causes the primacy effect? Monitor the Input/Output boxs Messages view. Why does the model sometimes recall the same word twice in the same trial? The serial position curve still doesnt look like the one in the introduction. Characterise any differences. Can you account for them?

36 3: Hands-on Session 15: :45

37 Exploring the Modal Model: Decay, Time & Rehearsal: I 1. Add decay to LTS. Explore different decay functions and rates. 2. Double the rehearsal rate by adding a copy of the rehearsal rule. What happens if a third copy of the rehearsal rule is added? 3. All memorised words are currently recalled in parallel. Try rewriting the recall rule to make the recall process serial.

38 Exploring the Modal Model: Decay, Time & Rehearsal: II The serial recall rule:

39 Exploring the Modal Model: Decay, Time & Rehearsal: III 1. Explore the effect of the Buffer Access property of each buffer. Play with these (and other) parameters to see how they affect the models behaviour. 2. The Experimenter system is written using standard COGENT. Try to discover how it works. 3. Find a principled solution to the problem of stopping rehearsal when recall commences.

40 Beyond the Modal Model: COGENT Web Archives If you have access to the web, select View CogWeb… from the programme manager and download and explore some other models

41 4: Supplementary Topics 16: :15

42 Advanced COGENT Features: Experiment Scripting

43 Connectionist and Hybrid Modelling in COGENT

44 Implementing Soar / ACT-R in COGENT Why? 1. Fast prototyping of possible architectural changes 2. Development and exploration of variant architectures in which some basic assumption is denied

45 Soar 8: Component Processes

46 ACT-R 5.0: Component Processes

47 COGENT Version 3: Planned Features 1. Fresh look and feel 2. Additional drawing tools 3. Improved navigation facilities 4. Revised box / object hierarchy 5. Improved efficiency on Windows platforms Public release of V3.0 expected by end of 2007

48 COGENT Version 3: Look and Feel

49 COGENT Version 3: Additional Drawing Tools Add annotations Nudge objects Stretch objects Zoom

50 COGENT Version 3: Navigation Facilities

51 COGENT Version 3: Revised Object Hierarchy Compound Process (accepts input; generates output) Rule-based Network (feed-forward, recurrent) Buffer (accepts input; can be queried) Propositional (symbolic, analogue, tabular; …) Settling network Interface Input (prompt, script, socket) Output (pop-up, script, socket)

52 COGENT Version 3: Efficiency Improvements The model execution engine is written in Prolog: Good for rule-based processes Inefficient for all other component types Efficient implementations (written in C) of some internal functions are available when running COGENT from a Unix-based OS These will be extended and incorporated into the Windows version

53 Selected References Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. In Spence, K. W., & Spence, J. T. (Eds.), The psychology of learning and motivation: Advances in research and theory. Orlando. FL: Academic Press. Atkinson, R. C., & Shiffrin, R. M. (1971). The control of short term memory. Scientific American, 225, 82–90. Cooper, R. P. (2007). Integrating cognitive systems: The COGENT approach. In Gray, W. D. (Ed.). Integrated Models of Cognitive Systems. (pp ). New York: Oxford University Press. Cooper, R. (2002). Modelling High-Level Cognitive Processes. With contributions from Peter Yule, John Fox and David W. Glasspool. Lawrence Erlbaum Associates, Mahwah, NJ. Cooper, R., & Fox, J. (1998). COGENT: A visual design environment for cognitive modelling. Behavior Research Methods, Instruments, & Computers, 30 (4), 553–564. Glanzer, M., & Cunitz, A. R. (1966). Two storage mechanisms in free recall. Journal of Verbal Learning and Verbal Behavior, 5, 351–360. Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 6 3, 81–97. Postman, L. & Phillips, L. W. (1965). Short-term temporal changes in free recall. Quarterly Journal of Experimental Psychology, 17, 132–138.


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