Introduction to SOAR

Based on “a gentle introduction to soar: an Architecture for Human Cognition” by Jill Fain

Lehman, John Laird, Paul Rosenbloom.Presented by

Roman Ilin

Unified Theories of Cognition

• 1980, Newell started the project

• Task: to find a set of computationally realizable mechanisms and structures that can answer all the questions about cognitive behavior

Architecture

• Analogy with computer hardware (fixed) – software (changeable)

• BEHAVIOR = ARCHITECTURE + CONTEXT• Architecture reflects designer’s assumptions about the

context.• In general, Architecture is a theory of what is common

among much of the behavior at the level above it.• Cognitive Architecture is a theory of the fixed

mechanisms and structures that underlie human cognition.

• SOAR is a cognitive architecture

What cognitive behaviors are common?

1. Goal oriented2. Reflects a rich, complex, detailed

environment3. Requires a large amount of knowledge4. Requires use if symbols and abstractions5. Flexible and a function of the

environment (real time)6. Requires learning from the environment

and experience

CONTEXT

CONTEXT

• BEHAVIOR = ARCHITECTURE + CONTEXT• CONTEXT is a theory about the knowledge the agent

has that contributes to the behavior

Example of knowledge categories

Behavior as Movement through Problem Spaces

Formalize problem space – goal, states and operators, and the principle of rationality

Connecting Content (knowledge) to Architecture

• Need Domain Independent Level of knowledge description

• It is “Goal Context” – a set of four (kinds of) things.

• {goals, problem spaces, states, operators}

• Knowledge is represented in terms of the above four things

Goal Context

Note, Single structure can be used for both “acting” and “thinking about acting”

Memory, Perception, action and Cognition

• Long Term Memory (LTM) – knowledge that is independent of the current goal

• Working Memory (WM) – current occurrence of some portion of that knowledge

• Decision Cycle – to tie LTM to WM

LTM – if – then statements

Decision Cycle – two phases

• Elaboration– Contents of WM are matched against the IF

parts of LTM

• Decision– Select of the suggested operators

What if decision cannot be made?

• Impasse results in switching the problem space

• SOAR defines fixed set of domain independent impasses.– Resolve tie impasse– Fail to decide impasse– …

Finding Solution using sub goal

• two more operators– Augment– Evaluate

Augment

Evaluation Operator

LEARNING, FINALLY• Practice improves what we do• Since behavior = architecture + content• And architecture is fixed• Content must change (learn)• Do it by adding new entries in LTM• Creates a “Chunk” by using parts of the environment

existing in pre-impasse environment that were used to achieve the result

• Chunking is deductive learning

Putting it all together

ROBO SOAR: An Integration of external interaction, planning.

And learning using Soar.John . E. Laird, Eric. S. Yager, M.

Hucka, C. M. Tuck, 1991

Presented by Roman Ilin

THE ROBOT AND ITS TASKS

Capabilities

• Problem Solving with Incomplete Information

• Problem solving with delayed perception• Planning• Learning from external guidance• Interruption and reactivity• Improve efficiency• Improve correctness

System Architecture

Primitive Operators – commands sent to the robot controller (snap-in, snap-out not shown)

Initial Operators

• ALIGN-BLOCKS

• TURN-OUT-LIGHT

• Light has a preference

• Initially the operators will lead to impasses and learning.

Example of problem solvinggoals: align-blocks, align block-pair, puma-arm-

command

Guided Problem Solving – planning Idepth first guided search.

Guided Problem Solving – planning Ichunking

Refining Knowledge Itriangular blocks

Refining Knowledge IItriangular blocks