Intelligent Robotics
CIS480
January 16, 2007

 Artificial Intelligence

Study intelligence

Apply – design intelligent systems
 to better serve mankind
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 Robot

Embodied

Autonomous

Agent
 Intelligent robot
 +
Intelligent
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Embodied
 Situated

Located in the world
 Sensor (receptor)
 Receive “raw” information about world
 Effector (actuator)

Accomplish an action
» with respect to self
» with respect to world
 “one who brings about a result or event; one who accomplishes a purpose”
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Autonomous
 Autos :: self
 Nomos :: law
 Definition

Self-governing
» Note: The term cybernetics stems from the Greek
Κυβερνήτης (kybernetes, steersman, governor, pilot, or rudder — the same root as government).

Independent in mind or judgment

Self-directing

Not controlled by others or outside forces
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 Definition

One that acts or has power/authority to act

One that represents another

Root meaning – one that acts or exerts power

Means of effecting a result
 Software agent ( David Croft )

Delegacy – discretionary authority
 Competence

Amenability – ability to adapt
 Software resident
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



Many definitions
MSN Encarta
: “general mental capability to reason, solve problems, think abstractly, learn and understand new material, and profit from past experience. Intelligence can be measured by many different kinds of tasks . . . Intelligence draws on a variety of mental processes, including memory, learning, perception, decision-making, thinking, and reasoning.”
Einstein: “Imagination is more important than knowledge.”
Henk Tuten: “complex use of creativity”
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 Another view
 Creative simplicity
 Examples

Every mileage divisible by 3000

Cutting the Gordian knot

Efficient use of cars
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 Sense
 Plan
 Act
 Perhaps a 4 th – Learn
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 Serve

Act
 Autonomous

Sense
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 The most basic ::

Act

Sense
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 Serve

Act
 Autonomous

Sense
 Changing environment

Plan
 Plan

Reason
 Plan

Represent knowledge
 Knowledge

Learning
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 Sense
 Act
 Represent knowledge
 Reason
 Learn
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
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Chapter One
I. Robotic Paradigms
1. From Teleoperation to Autonomy
1.1 Overview
1.2 How Can a Machine Be Intelligent?
1.3 What Can Robots Be Used For?
1.3.1 Social implications of robotics
1.4 A Brief History of Robotics
1.4.1 Industrial manipulators
1.4.2 Space robotics and the AI approach
1.5 Teleoperation
1.5.1 Telepresence
1.5.2 Semi-autonomous control
1.6 The Seven Areas of AI
1.7 Summary
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 Linguistics

A pattern of conjugation or declension to memorize which serves as a template for a class of words.
 Thomas Kuhn

Shared scientific theories

Common methods of solving problems

Common norms for scientific activity

Shared metaphysics
 Current usage

Example, pattern

Conjugation, declension

Theoretical framework
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Paradigm – current usage
 Merriam-Webster:
Main Entry: par·a·digm
Pronunciation: 'per-&-"dIm, 'pa-r&also -"dim
Function: noun
Etymology: Late Latin paradigma, from Greek paradeigma, from paradeiknynai to show side by side, from para+ deiknynai to show -- more at DICTION
1 : EXAMPLE , PATTERN ; especially : an outstandingly clear or typical example or archetype
2 : an example of a conjugation or declension showing a word in all its inflectional forms
3 : a philosophical and theoretical framework of a scientific school or discipline within which theories, laws, and generalizations and the experiments performed in support of them are formulated; broadly : a philosophical or theoretical framework of any kind
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The Structure of Scientific
Revolutions
 Stanford Encyclopedia of Philosophy ::
“one of the most cited academic books of all time”

Development of “science”

Not
» Steady cumulative progress
» Ever closer approximation to “truth”

Normal phase

Revolutionary (extraordinary) phase
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 Normal

Ruling paradigm

High degree of conceptual uniformity

Steady progress in:
» Accretion of knowledge
» Solving existing “puzzles”
 Pre-revolutionary :: mounting set of anomalies
 Revolutionary :: paradigm shift

Alternative paradigm(s) proposed

Period of competition

Resolution – old paradigm dies out
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 Observation is theory-laden
 Observation language and theory language deeply interwoven
 Historical & contemporary comprehension deeply interwoven
 Sought logic of discovery
 Note :: key issues for robotics
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 Norwood Russell Hanson


Perception is theory-laden

Rock or clump of algae?

Optical illusions

Duck or rabbit ?

Wiki article

Triangle puzzle
Ệ theoretical incommensurability

Hanson

Kuhn
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Theory-laden-ness
 Gestalt shift
 From sensor data to percept
 Role of theory

Pre-process sensor data

Organize percepts

Basis of discovery plans
 Reasoning

Deduction (includes mathematical induction)

Induction

Abduction
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Theory-laden-ness Examples
 Recognition

Embodied

Autonomous

Agent
 Critical nature of perceptology

Shadow vs. cliff

Rock vs. algae

The Measures Taken , Brecht
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 Design
 Basic components
 Teleology
 Component interaction
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 Design – the oft missing component in software
 Basic components

Logos – logic, internal structure, organizing principle

Telos – goal, purpose, objective, aim, function, intention, reason

Teleios – complete, finished, mature, perfected
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 The philosophical study of purpose

The triad’s central relational kernel
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 Reference
 Logos
 Mind, understanding

Comprehend need
 Generate purpose
 Create design

Determine level of achievement
 Telos

Provides focus
 Provides measure of efficacy of design
 Teleios
 Circumscribes design
 Measures artifact utility
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Knowledge Representation for
Intelligent Agents
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