The GLAIR Architecture for Cognitive Robotics
description
Transcript of The GLAIR Architecture for Cognitive Robotics
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The GLAIR Architecturefor Cognitive Robotics
Stuart C. ShapiroDepartment of Computer Science & Engineering
and Center for Cognitive ScienceState University of New York at Buffalo
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GLAIR:Grounded Layered Architecture
with Integrated ReasoningFocus of This Talk:
ConnectingReasoning Mind
withActing/Sensing Body
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Motivations• Add acting and sensing to a reasoning agent.
– First person reasoning; on-line acting & sensing.• Layers
– Motivated by mind/body connections/distinctions.– Let same mind be plugged into different bodies.
• Embodiment– Origin of beliefs in sensation & proprioception.– First-person privileged knowledge of own body.
• Situatedness– Has a sense of where it is in the world.
• Symbol grounding– In body-layer structures.– Symbol as pivot between various modalities.
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Outline
The Layers
Symbol Grounding
Putting it Together: Two examples
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KL
PMLa
PMLb
PMLc
SAL
Mind
BodyIndependentof lower-body
implementation
Hearing
Vision
Motion
Speech WORLD
I/P s o c k e t s
GLAIR Architecture
Dependenton lower-bodyimplementation
Proprioception
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Sensori-Actuator Layer
• Sensor and effector controllers
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Perceptuo-Motor Layer
• PMLa• PMLb• PMLc
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PMLc
• Abstracts sensors & effectors• Body’s behavioral repertoire
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PMLb
• Translation & Communication– Between PMLa & PMLc
• Highest layer that knows body implementation
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PMLa• Grounds KL symbols
– Perceptual structures– Implementation of primitive actions
• Registers for Embodiment & Situatedness– Deictic Registers– Modality Registers
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The Knowledge Layer• Implemented in SNePS• Agent’s Beliefs• Representations of conceived of entities• Semantic Memory• Episodic Memory• Quantified & conditional beliefs• Plans for non-primitive acts• Plans to achieve goals• Beliefs re. preconditions & effects of acts• Policies: Conditions for performing acts• Self-knowledge• Meta-knowledge
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SNePS
• A KRR system• Every non-atomic expression is simultaneously
– An expression of SNePS logic– An assertional frame– A propositional graph
• Every SNePS expression is a term– Denoting a mental entity
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Ontology of Mental Entities• Entity
– PropositionAgent can believe it or its negationIncludes quantified & conditional beliefs
– ActAgent can perform it
– PolicyCondition-act rule agent can adopt
– ThingOther entities: individuals, properties, times, etc.
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Outline
The Layers
Symbol Grounding
Putting it Together: Two examples
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Entities, Terms, Symbols, Objects
• Agent’s mental entity: a person named Stu
• SNePS term: b4
• Object in world:
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AlignmentMind (KL)
Body (PML/SAL)
World
KL term
PML structure
Object/Phenomenon Action
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World Objectsto Feature Tuples
<Height, Width, Texture, . . . >
WorldPML/SAL
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Feature Tuplesto KL Terms
<Height, Width, Texture, . . . >
PML/SALKL
ProperName(b4, Stu)
Alignment
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Incomplete PML-Descriptions
<Height, nil, nil, . . . >
PML/SALKL
Height(b4, b12)
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Unifying PML-Descriptions
<x, nil, nil, ... >
PML/SALKL
b20
b30
b31
b6
<nil, y, nil, ... >
<nil, nil, z, ... >
<x, y, z, ... >
Isa
Prop
Prop
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Deictic Registers
For being situated in the worldPML registers hold KL terms
I term denoting agentYOU term denoting dialogue partnerNOW term denoting current time
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Modality Registers
For privileged first-person knowledge of what agent is doing
Register for each modality, m, holdsKL term denoting act that m is engaged in
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Outline
The Layers
Symbol Grounding
Putting it Together: Two examples
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<green, nil>
PML/SALKL
b20
b30
b6
<nil, robotic>
Isa
Prop
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Find a green robot.
(find )
cassie
m75
m76
robbie
<green, robotic>
VISION
Language-Mind-World-Mind
WORLD
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Building Episodic Memory
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KL
PML
e1
I
a1 b1
m1!
t1 e2
a2
m2!
t2
m3!
NOWCOUNT n
hom0
qm4!
before afterevent eventtime
time
time
act act
agent
agent
duration
ACT
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Summary
• GLAIR is an architecture:– To connect mind and body
• For symbol grounding– To provide first-person privileged knowledge of
• The body• What it’s doing
– To provide situatedness in the world• Via deictic registers
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Collaborators
Past and present members ofSNeRG: The SNePS Research Grouphttp://www.cse.buffalo.edu/sneps/