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Embodiment 11/27/06 23:27
1
11/27/06 UH 267 — Embodiment 1
Embodiment &Embodiment & SituatednessSituatedness
11/27/06 UH 267 — Embodiment 2
How Dependent is Intelligenceon its Hardware?Traditional View
• Brain is no more powerful than Turing machine• Human intelligence is a result of the program
running on our brains• The same program could be run on any Universal
TM• In particular, it could run on a Von Neumann
machine and make it artificially intelligent
11/27/06 UH 267 — Embodiment 3
ConnectionistView
• Information processing on Von Neumanncomputers (hardware) is fundamentally differentfrom that in brains (wetware)
• The flexible, context-sensitive cognition weassociate with human intelligence depends on thephysical properties of biological neurons
• Therefore, true artificial intelligence requiressufficiently brain-like computers(neurocomputers)
11/27/06 UH 267 — Embodiment 4
Importance ofEmbodied Intelligence• Traditional (dualist) view: mind
is essentially independent of the body– in principle, could have an intelligent “brain in a vat”
• Now we understand that much of our knowledgeis implicit in the fact that we have a body
• Also, our body teaches us about the world• Structure of body is foundation for structure of
knowledge• A “disembodied intelligence” is a contradiction in
terms?
11/27/06 UH 267 — Embodiment 5
Structure ofEmbodied Intelligence
• Representational primitives are skills, notconcepts
• Higher-level skills are built on lower-level
• Lowest-level skills are grounded in the body
11/27/06 UH 267 — Embodiment 6
Embodied & SituatedArtificial Intelligence
• Therefore a genuine AI must be:– embedded in a body (embodied)– capable of interacting significantly with its
world (situated)• Intelligence develops as consequence of
interaction of body with environment,including other agents
• How can we investigate embodied, situatedintelligence?
Embodiment 11/27/06 23:27
2
11/27/06 UH 267 — Embodiment 7
“Ant” Microrobots (Brooks, MIT)• About 1 cubic inch• 17 sensors• Can communicate with
each other• Goal: push limits of
microrobotics• Goal: explore social
interactions inspired byant colony
• Applications: explosivesdisposal, Mars exploration
11/27/06 UH 267 — Embodiment 8
Clustering Around “Food”
• “Food” amongst otherobjects in environment
• First “ant” toencounter food,signals others
• Others cluster at foodsource
11/27/06 UH 267 — Embodiment 9
Tag Game
• “It” robot wandersuntil bumps something
• Transmits “Tag”• A “Not It” robot
replies “I got tagged”• First becomes “Not It”• Second becomes “It”
11/27/06 UH 267 — Embodiment 10
Genghis (Brooks, MIT)• Inspired by evolution
in that more complexbehaviors build onsimpler ones
• Individual legs “dotheir jobs”
• Legs are coordinatedto achieve stability
• Leg motioncoordinated to achievelocomotion to goal
11/27/06 UH 267 — Embodiment 11
Genghis (Brooks, MIT)
Front view & infrared sensing of person
11/27/06 UH 267 — Embodiment 12
Cog (Brooks, MIT)• “Humanoid
intelligence requireshumanoid interactionswith the world”
• Form of body isfundamental tocognitiverepresentation– no “brains in vats”
• Human-likeintelligence requireshuman-like body
Embodiment 11/27/06 23:27
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11/27/06 UH 267 — Embodiment 13
Learning Hand-Eye Coordination
• Before learning toreach to a visual target
• Final position of handdifferent from wherelooking
11/27/06 UH 267 — Embodiment 14
Learning Hand-Eye Coord. (2)• View from Cog’s eyes
during training trial• Cog learns to
coordinate appearanceof arm’s position with“feel” of arm’sposition
• Rapid motion issaccade
• Also see motion-detection & groupingalgorithm
11/27/06 UH 267 — Embodiment 15
Learning Hand-Eye Coord. (3)• After 3 hours self-
training• Robot instructed to
reach toward anymoving object
• Successfully reachestowards object
• (Hand is non-functional)
11/27/06 UH 267 — Embodiment 16
Cog: “Social Interaction”
• Cog attending tovisual motion
• Orients head & eyes tomotion
• (Arm & hand motionare not relevant tointeraction)
11/27/06 UH 267 — Embodiment 17
Cog: Learning by Imitation• Imitation is an
important means ofhuman learning
• Here, Cog learns toimitate head motions
• Recognizes the motionof faces
• Cog does not try toimitate non-faces
11/27/06 UH 267 — Embodiment 18
Cog: Learning by Imitation (2)
• Cog recognizesobjects sufficientlylike faces
• Imitates their motionwith its own
Embodiment 11/27/06 23:27
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11/27/06 UH 267 — Embodiment 19
Interactions with Other Agents
• Being situated includes interactions withother agents
• Cooperative interactions:– robots with robots– robots with humans
• Competitive interactions:– robots against robots– robots against humans– robots against animals “Robonaut”
11/27/06 UH 267 — Embodiment 20
“Mind Reading”and Other Social Skills
• Need to understand other agents’ mentalstates & processes
• Need to communicate (or misrepresent)one’s own mental state & processes
• Non-verbal communication: gesture, eyecontact, gaze
• Imitation as basis of learning & socialunderstanding
11/27/06 UH 267 — Embodiment 21
Shared Cooperative Activities
• Commitment to joint activity & mutualsupport
• Joint intention theory• Simulation theory• Ability to take perspective of other agent
11/27/06 UH 267 — Embodiment 22
Kismet (Brooks, MIT)
• Responds to a facewith a happyexpression
• Responds to rapidlymoving face withdisgusted expression
11/27/06 UH 267 — Embodiment 23
Kismet (Brooks, MIT)
• Two-wayconversationalinteraction
• Kismet understandsintonation & bodylanguage, but notwords
11/27/06 UH 267 — Embodiment 24
Kismet (Brooks, MIT)
• Example of three-wayconversationalinteraction
Embodiment 11/27/06 23:27
5
11/27/06 UH 267 — Embodiment 25
Leonardo
• Cynthia Breazeal’sLab, MIT
• “Sociable Robots”Project
• Vehicle for exploringsocially guidedlearning & cooperativeactivity
(video < Breazeal’s Lab)
11/27/06 UH 267 — Embodiment 26
Touch-Sensitive “Skin”• Touch-sensitive
silicone skin over entirebody
• Mapped to neural net-like “homunculus”
• Here Leo isprogrammed to notice& withdraw fromcontact
(video < Breazeal’s Lab)
11/27/06 UH 267 — Embodiment 27
Learning to Mimic Expressions• Imitation as a way to bootstrap social understanding
& “theory of mind”• Understand behavior in terms of mental states
producing it• Leo makes faces• Human imitates• Leo learns what his
face looks like• Learns to imitate humans
(video < Breazeal’s Lab)
11/27/06 UH 267 — Embodiment 28
Socially Guided Learning
• Leo is taught to “turnon all the lights”
• Leo generalizes tonew situation
• Leo displayscommitment to jointactivity in spite ofincorrect action
(video < Breazeal’s Lab)
11/27/06 UH 267 — Embodiment 29
Social Implications ofArtificial Intelligence