almondpitterpatterAI and Robotics

Feb 23, 2014 (4 years and 4 months ago)


Adaptive Robotics


Autumn Semester 2008

Lecturer: Amanda Sharkey


the word “robot” comes from the play
`Rossum`s Universal Robots`, by
Czech writer Karel Capek (1921)

Robot, from robota, “servitude,
forced labour, drudgery”

Robots rebel, and kill all humans

What is a robot?

Joseph Engelberger, a pioneer in
industrial robotics: "I can't define a
robot, but I know one when I see

Brady (1985)

“the intelligent connection of
perception to action”

Arkin (1998)

“An intelligent robot is a machine able
to extract information from its
environment and use knowledge
about its world to move safely in a
meaningful and purposive manner”

Robotics Industry Association:

“a robot is a re
programmable, multi
functional, manipulator designed to move
material, parts, tools or specialised
devices through variable programmed
motions for the performance of a variety
of tasks”

(excludes mobile robots!)

Changing definitions

Stop fearing the robot

stop making a man of him! Just
remember that the sewing machine is a robot, the automobile is
a robot, the electric car and the phonograph and the telephone
are all robots. Each one men have developed in order to
unburden themselves of some onerous task and on to better
things. Each one does a specific job, and no more. Why begin
now to worry about robots when we have been enjoying their
services for centuries?

Woodbury, D. (1927)
Dramatising the

New York Times, Nov 1st

Like Wittgenstein and “games”

No single feature shared by the many
examples, but rather “
a complicated
network of similarities, overlapping and
” [Wittgenstein, 1953].

The same is also true of ‘robot’

various examples bear family
resemblances rather than a single

Different groups of robots

Autonomous robots

Industrial robots

like robots

configurable robots

Biological models

Toys and companions

Course Aims

To present the key concepts of a recent
approach to AI

And contrast to earlier approaches

To consider the underlying mechanisms
for robot control

To inform about research in robotics

What are the motivations?


Biological inspiration

Biorobotic modelling

Understanding intelligence

Teaching Method

Lectures, and assignment.

See website for course (Lecturer’s
module pages)

Assessment: Exam and assignment

Background Reading

Clark, A. (1997) Being There: Putting Brain, Body
and World Together Again. A Bradford Book,
MIT Press

Franklin, S. (1995) Artificial Minds: A Bradford
Book, MIT Press

Nolfi, S. and Floreano, D. (2000) Evolutionary
Robotics: The biology, intelligence and
technology of self
organising machines. A
Bradford Book, MIT Press

Pfeifer, R., and Scheier, C. (2001) Understanding
Intelligence, MIT Press

Why robotics?

Can we create artificial beings?

Are we machines?

How do we work?

Understanding by building

Making robots to perform useful tasks

Robots as companions?

What is Adaptive Robotics?

Recent approach to AI

Reflected in

Behaviour based robotics

Reactive robotics

Evolutionary robotics

Artificial Life

Swarm Intelligence and swarm robotics

Embodied cognition

Different views of mind and

Emphasis on Mind and Reasoning
independent of world (

How can mind emerge from the workings of
a physical machine? (brain)

Relationship between brain, body, mind and
world…. (
embodied cognition

Three Stage Progression to current
emphasis on Embodied Cognition

Classical Cognitivism or
computationalism (late 1950’s to

Connectionism (main period


Embodied Cognition and Adaptive
Intelligence (1990’s to present)

N.B. dates only a rough guide

1. Computationalism

Mental states = computational states

Good Old Fashioned Artificial Intelligence

Physical Symbol System Hypothesis (Newell
and Simon, 1976)

A physical symbol system is a necessary and
sufficient condition for general intelligent action.

intelligence is symbol manipulation

computers manipulate symbols

computers can be intelligent

1. Computationalism cont.

Memory as retrieval from stored
symbolic database

Problem solving as logical inference

Cognition as centralised

Environment just a problem domain

Body as an input device



“The mind is to the brain as the
program is to the hardware”
Laird, 1988)


hardware/software distinction

we are interested in the software

could run on any hardware (Swiss

2. Connectionism

Neural nets

An account of mental states in terms
of neurons

related to brain

Memory as pattern recreation

Problem solving as pattern
completion and transformation



3. Embodied Cognition

As connectionism PLUS

Environment as active resource

Body as part of computational loop

Brain, body, world intricately

3. Embodied cognition cont.

Gradual move away from
anthropocentric view

Greater awareness of abilities of
human organisms, and their
abilities to interact with and survive
in the world.

Early mobile robots: Shakey

Shakey the Robot

Developed by SRI (Stanford Research
Institute) from 1966

First mobile robot to visually interpret,
and reason about its surroundings

TV camera, range finder, bump sensors

Programs for sensing, modelling and

Example task: “push the block off the

Stanford Cart

TV cameras: took pictures of scenes,
and planned path between obstacles






“Intelligence without representation”

Realisation that mobility, vision and
ability to survive are important
aspects of intelligence

Brooks and idea of Creatures

Able to cope with changing and
uncertain world

Should have goals, and purpose in

“An ant, viewed as a behaving system, is quite
simple. The apparent complexity of its
behavior over time is largely a reflection of the
complexity of the environment in which it
finds itself”

Herbert A. Simon, 1969

Idea of
responses to the world, instead
of modelling and planning.

Intelligence is determined by the dynamics of
interaction with the world.

Key concepts in new
approach to AI

a) Reactive behaviour

b) Adaptivity

c) Situatedness

d) Embodiment

e) Emergence and Self

Changing view of intelligence

a. Reactive Intelligence

Arkin (1995): hallmark characteristics

emphasis on behaviours and simple
sensorimotor pairings

Avoidance of abstract representational
knowledge (time consuming)

Animal models of behaviour

Demonstrable results: walking robots,
crawling robots, military robots etc.


Biological inspiration:

e.g. birds flocking,

ants foraging.


Grey Walter (1953) electronic tortoise.

Braitenberg (1984) synthetic psychology

Brooks (1986) behaviour
based robotics
and subsumption architecture.

b. Adaptivity

Adaptivity: ability to adjust oneself to the

Physiological adaptation

e.g. sweating
to adjust to heat

Evolutionary adaptation

e.g. peppered
moth. Light in colour, in industrial area
became dark in colour

Sensory adaptation

e.g. our pupils
adjusting to poor light

Adaptation by learning

e.g. where food
is found

c. Situated

An emphasis on robot’s interaction
with its environment (related to

Brooks (1991) “the world is its own
best model”

A situated agent must respond in a
timely fashion to its inputs.

d. Embodiment

Physical grounding of robot in the world

Brooks (1991): embodiment of intelligent
systems critical because

Only an embodied intelligent agent is fully
validated as one that can deal with the
real world

Only through physical grounding can any
meaning be given to the processing
occurring within the agent

“Intelligence is determined by the
dynamics of interaction with the
world” (Brooks 1991)

embodied cognition

A solution to the symbol grounding

(remember Searle’s Chinese Room!)

e. Emergence

Adaptive success that emerges from
complex interactions between body,
world and brain

A non
centrally controlled (or
designed) behaviour that results
from the interactions of multiple
simple components

Meanings of the term

Surprising situations or behaviours

Property of system not contained in
any of its parts

Behaviour resulting from agent
environment interaction that is not
explicitly programmed.

Ant colony

Individual ants are simple and
reactive (?)

Emergent behaviour of colony is


An ant colony is self

individuals, local interactions, emergent
behaviour .. No global control

organisation is a set of dynamical mechanisms whereby
structures appear at the global level of a system from
interactions among its lower
level components. The rules
specifying the interactions among the system’s constituent
units are executed on the basis of purely local information,
without reference to the global pattern, which is an
emergent property of the system rather than a property
imposed upon the system by an external ordering

(Bonabeau, Dorigo and Theraulaz, 1999)

Frisbee collecting robots

Robots in an arena + frisbees

Simple rules

Emergent result

clustering and
sorting of frisbees.

Changing view of intelligence


emphasis on reasoning,
planning, and representation.
centred (anthropocentric)

based robotics and
beyond: emphasis on simpler
organisms and their ability to
survive in the world.


For this week and next.

Brooks, R.A. (1991) Intelligence without Reason.
Proceedings of 1991 International Joint
Conference on Artificial Intelligence, 569

Robots in the news

Murata Manufacturing: Murata boy

controlled by blue tooth, and can
ride a bike forwards and backwards.

9/25/2008 12:23 PM


iRobot Corp. (IRBT:
), on Thursday, said
that it has received an additional $13.3 million
order from the US Army for PackBot 510 with
FasTac Kit robots for carrying bomb
identification and other life
threatening missions.