ACT-R Workshop
John R. Anderson
Daniel Bothell
Christian Lebiere
Niels A. Taatgen
Schedule of Events:
9:00-10:30: ACT-R from CMU’s Perspective
11:00-12:30: Architecture
1:30-3:30: Extensions
4:00-5:30: Future of ACT-R from a non-CMU Perspective
And lots of Interaction!
ACT-R Workshop Schedule
Opening: ACT-R from CMU’s Perspective
9:00 - 9:45 Overview of ACT-R -- John R. Anderson
9:45 – 10:30 Details of ACT-R 6.0 -- Dan Bothell
Break: 10:30 – 11:00
Presentations 1: Architecture
11:00 – 11:30 Functional constraints on architectural mechanisms -- Christian Lebiere
11:30 – 12:00 Retrieval by Accumulating Evidence in ACT-R -- Leendert van Maanen
12:00 – 12:30 A mechanism for decisions in the absence of prior reward -- Vladislav D.
Veksler
Lunch: 12:30 – 1:30
Presentations 2: Extensions
1:30 – 2:00 ACT-R forays into the semantic web -- Lael J. Schooler
2:00 – 2:30 Making Models Tired: A Module for Fatigue -- Glenn F. Gunzelmann
2:30 – 3:00 Acting outside the box: Truly embodied ACT-R -- Anthony Harrison
3:00 - 3:30 Interfacing ACT-R with different types of environments and with different
techniques: Issues and Suggestions.-- Michael J. Schoelles
Break: 3:30 – 4:00
Panel: 4:00 – 5:30: Future of ACT-R from a non-CMU Perspective
Danilo Fum, Kevin A. Gluck, Wayne D. Gray, Niels A. Taatgen, J. Gregory Trafton,
Richard M. Young
Overview of ACT-R
John R. Anderson
Carnegie Mellon University
Outline:
9:10: Big picture of what ACT-R is about
9:20: Evolution of the Procedural Module
9:30: Evolution of the Declarative Module
9:35: How ACT-R spreads
ACT-R is Not Monolithic
1. It is a community brought together by common theoretical
assumptions and a commitment to the “No Magic” Principle -cognitive theory has to run and it has to predict data. While ACT-R
may be sustained from CMU it no longer resides at CMU. The
community motto is “Let a thousand flowers grow”
2. It is a set of software for purposes of simulation. This software
consists of a core LISP implementation, but there are many
theoretically-motivated extensions and alternative practicalitymotivated alternative implementations. In some cases the software
provides the best definitions of what the theoretical claims are.
3. It is a theory that attempts to formalize and operationalize certain
aspects of our understanding of the human mind. This includes
assumptions that are more core and those that are more peripheral.
It changes as our knowledge grows and has different interpretations
in different hands.
ACT-R: The Oldest Core Principles
1. The Procedural-Declarative Distinction
a. The declarative component originated in Anderson & Bower (1973)
HAM network representation of memory.
b. The procedural component originated in Newell’s (1973) production
system theory of cognitive control.
c. Both the procedural and declarative components have evolved far
from these origins.
2. The Symbolic-Subsymbolic Distinction
a. In addition to the symbolic level that represented knowledge there
is a subsymbolic level that controls access to that knowledge.
b. The subsymbolic level was initially designed to reflect the 1970s &
1980s ideas about neural processing.
c. Guided by rational analysis the subsymbolic level was updated in
1993 to reflected the likelihood that the information was useful.
This was the birth of ACT-R.
Evolution from ACT-R 2.0 (1993) to
ACT-R 6.0 (2007)
1. There were 3 driving forces:
a. The emergence of a user community around the publicly available
ACT-R 2.0.
b. The realization that the “No Magic” principle required that we be
able to model the processing all the way from input to output.
c. The insistence on not making assumptions that could not be
cashed out into neurally plausible computations.
2. This converged in the modular architecture of ACT-R 6.0:
a. The allowed community members to try variations on existing
ideas and extensions but keep what they wanted.
b. We borrowed the modular organization of EPIC for the
perceptual-motor modules.
c. There was growing evidence that, while the brain was a complex
parallel machine, different regions had their specializations.
Modules are high
capacity, parallel,
and asynchronous
Modules in ACT-R 6.0
Goal
Imaginal
Buffers provide narrow paths
of communication -- only hold
a chunk in ACT-R terms.
Declarative
Procedural
Aural
Visual
Production system that
contains rules that
recognize patterns and
react
Manual
Vocal
ACT-R Module-Region Mappings
Outline:
9:10: Big picture of what ACT-R is about
9:20: Evolution of the Procedural Module
9:30: Evolution of the Declarative Module
9:35: How ACT-R spreads
The Procedural Component in
ACT-R has Evolved from Computer
Science Notation to Description of
the Brain’s Action Selection
600517
- 23523
4
The First Real ACT-R Production Rule
If the goal is to process a column
and the top digit is not smaller than the bottom digit,
Then write the difference between the digits as the answer
Responds to a Particular
Pattern that Appears in the
Buffers of a Set of Modules
Goal>
Task: Process-Column
Imaginal>
Top:
7
Relation: >=
Bottom: 3
Selects an
Action
Which consists of
requests to other Modules
Goal>
Task: Subtracting
Request
Difference
Declarative>
Type: subtraction
Minuend: 7
Subtrahend: 3
The Second Real ACT-R Production Rule
If the goal is to process a column
and the top digit is not smaller than the bottom digit,
Then write the difference between the digits as the answer
Responds to a Particular
Pattern that Appears in the the
Buffers of a Set of Modules
Goal>
Task: Subtracting
Declarative>
Type: subtraction
Difference: 4
Selects an
Action
Which consists of
requests to other Modules
Goal>
Task: Next-column
Harvest
Difference
Manual>
Action: write
Digit: 4
Attributes of Production Rules
 Production rules are stimulus-response bonds that have “gone
over to the cognitive side” because among the stimuli they
respond to are past memories, mental images, and control
states.
 Respond to conjunctions of elements in the various buffers.
 These buffers can represent relational structures -- e.g. A
above B.
 Note how innocuous the use of variables is -- it basically
copying information from one brain region to another.
Stewart, T.C. and Eliasmith, C. (2008). Building production systems with realistic
spiking neurons. 30th Annual Meeting of the Cognitive Science Society.
Stocco, A., Lebiere, C., & Anderson, J. R. (in revision). Conditional routing of
information to the cortex: A model of the role of basal ganglia in high-level
cognition. Psychological Review
Learning of New Production
Rules
New Problem Situations
Requires Deliberation
Declarative Representations
Interpreted
Analogy to Prior
Experiences (e.g.
Past Tense Model)
Deduction
From 1st
Principles
Following instructions
(e.g. Multicolumn
Subtraction)
Traces Feed Into
Production Compilation
Eventually
Produces
New Production Rules
Origin of One of the Subtraction
Rules
Goal>
Task: Process-Column
State: Imaginal
Retrieve
Operator
Retrieval>
Type: operator
Pre:
Top
State
>=
Feature
Bottom
Imaginal >
Relation:
Pre
Action
Subtract
Identity
Retrieval>
relation: subtract
arg1: top
arg2: bottom
post:
Goal>
Task:
Perform
Subtraction
Imaginal >
Top:
Bottom:
Request
Difference
Action
Type
Action
Retrieve
Type
Arg1
Operator
Op11-1
arg2
Object
Bottom
Referent
Post
State
Subtracting
Feature
Retrieval>
type: subtraction
minuend:
subtrahend:
Goal>
Task: Subtracting
Goal>
Task: Process-Column
Imaginal >
Top:
Relation: >=
Bottom:
Object
Top
Referent
Retrieval>
Type: subtraction
Minuend:
Subtrahend:
Production compilation
compresses generalpurpose processing of
knowledge into special
case rules -- replacing
deliberation by action.
Reinforcement of Competing Productions
Retrieve-Instruction (Reinforcement 10)
If the goal is to process a column
Then retrieve an operator for that kind of column
Request-Difference-Subtract (Reinforcement 14)
If the goal is to process a column
and the top digit is not smaller than the bottom digit,
Then subtract the bottom from the top
Request-Difference-Borrow (Reinforcement 14)
If the goal is to process a column
and the top digit smaller than the bottom digit,
Then add 10 to the top digit
and set as a subgoal to borrow from the column to the left.
Request-Difference-Wrong (Reinforcement 14 or 0)
If the goal is to process a column
Then subtract the smaller from the larger
Utility Learning
for Competing Productions
14
U (n)  Ui (n 1)  [Ri (n) Ui (n 1)]
12 i
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Instruction
Subtract
Borrow
Wrong
0
25
50
75
100
Experiences
Probability
Probability
10
Considerable simplification of ACT-R utility
8
learning based of reinforcement-like learning
Instruction
6
results from the basal ganglia
Subtract
Utiity
Every time a
rule created it is
rewarded with
of its
the utility
parent
4
Borrow
Wrong
2
0
1 0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0
25
50
Experiences
eUi / s
Pi 
Uj / s
e

j
75
Instruction
Subtract
Borrow
Wrong
Standard ACT-R soft-max rule for
choosing among productions according
to their noisy utilities
25
50
75

Experiences
100
100
Outline:
9:10: Big picture of what ACT-R is about
9:20: Evolution of the Procedural Module
9:30: Evolution of the Declarative Module
9:35: How ACT-R spreads
What has Happened to the
Declarative Component in ACT-R?
It has bifurcated into two completely separate things:
1. An increasingly watered-down set of principles for the
representation of knowledge, which comes to be the contents
of module buffers. This is clearly a place where important new
thinking is required.
2. An increasingly empirically well-founded set of principles (with
a foundation in rational analysis) for how the brain performs
controlled retrieval of information from declarative memory.
Buffers and Declarative Memory
 Buffers associated
with modules
provide narrow paths
Goal
of communication.
 The contents of the
buffers are called
Imaginal
Declarative
chunks.
 Records of these
chunks are placed
Procedural
in declarative
memory.
Aural
Visual
 These can be later
retrieved and placed
in the declarative
buffer.
Vocal
Manual
Chunk Activation Reflects Probability of Use
Environmental Equation:
Log(Posterior(i | C))  Log(Pr ior(i))   Log(Likelihood( j | i))
j C
Posterior odds that
memory i will be
needed in context C
Prior odds that i is
needed: recency
and frequency
Momentary Activation of memory i
Activation Equation:
Likelihood ratio of
element j in context
given i is needed
Weighting of Source j
Ai  Bi 
W S
j
ji
j C
Base-level Activation of memory i
Association Strength from j to i
Fan Experiment:
Pirolli & Anderson (1985)
S ji  S  ln( Fan)

Activation Level
Growth of Activation
Recognition Latencies
A i
Time  I  Fe
Recognition Time (ms.)
intercept
Re trieval Time Equation
latency scale
r = .986 is a parameter-free
measure of the match between
theory and data.
Outline:
9:10: Big picture of what ACT-R is about
9:20: Evolution of the Procedural Module
9:30: Evolution of the Declarative Module
9:35: How ACT-R spreads
Temporal Module: An Example of
How One Can Extend ACT-R
Gate
Accumulator
Memory
Start
Signal
Comparison
Declarative Module
Goal Buffer
Pacemaker
Gate
Start
Signal
Accumulator
Retrieval Buffer
Productions
Pacemaker
Matching
Selection
Problem Buffer
Execution
Visual Buffer
Manual Buffer
Visual Module
Manual Module
External World
Other Module Extensions for ACT-R
 Salvucci’s Emma Module for Eye Movements.
 My new Metacognitive Module.
 Spatial Modules (Gunzelmann, Harrison & Trafton).
 Fatigue Module (Gunzelmann) ????
 Reasoning Module LarKC (Schooler)????
Module Modifications
SNIF-ACT (Fu & Pirolli): Procedural and Declarative.
Threaded Cognition (Salvucci & Taatgen): Goal
Spacing Effect (Pavlik): Declarative.
Blending (Lebiere): Declarative.
 Race/A (van Maanen & Van Rijn): Declarative
Visual Saliency (Byrne): Visual.
Gray, Veksler, & and others of the RPI Co: Procedural.
Bothell & Leabra: Visual.
You Don’t Need to Change ACT-R to
Have an Interesting Model
Fum & Stocco: Sugar Factory
Lebiere, Wallach, & Taatgen: Sugar Factory
Altmann & Trafton: Tower of Hanoi
Lewis & Vasishith: Parsing
Taatgen: Acquistion Past Tense Model
Anderson (2007) & Everybody (recently): Everything in fMRI
And indeed most of the published ACT-R models.
Getting ACT-R out of the Narrow
Confines of Laboratory Experiments
Best & Lebiere: MOUT
St. Amant & Ritter: Segman
Bothell, Douglass, Lee: Unreal Tournament
Harrison & Trafton: Robotics
Destefano: Space Fortress
Schoelles: Lots of Interfaces
ACT-R is Not Monolithic
1. It is a community brought together by common theoretical
assumptions and a commitment to the “No Magic” Principle -cognitive theory has to run and it has to predict data. While ACT-R
may be sustained from CMU it no longer resides at CMU. The
community motto is “Let a thousand flowers grow”
2. It is a set of software for purposes of simulation. This software
consists of a core LISP implementation, but there are many
theoretically-motivated extensions and alternative practicalitymotivated alternative implementations. In some cases the software
provides the best definitions of what the theoretical claims are.
3. It is a theory that attempts to formalize and operationalize certain
aspects of our understanding of the human mind. This includes
assumptions that are more core and those that are more peripheral.
It changes as our knowledge grows and has different interpretations
in different hands.
(p. 12 Architecture of Cognition, 1983)
2007
Be Fruitful
and Multiply!