Chapter 6: Looking Glass World

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Chapter 6 Looking Glass World
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• Simulations in computers exist as
• Binary code
• Logic operations

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Approaches to coding

• Outside-in (math based)
• Inside-out (physics based)

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Outside-in

• it starts with how things should look and then
  tries to bolt on code for how it should behave.
• Special code must be added to account for
  imperfect behavior
• Example Bouncing Ball
• yabs(sinx) parabolas
• yabs(sinax)/bx decaying parabolas
• yabs(sinaxc)/bx friction

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Inside-out

• For this we must start from the inside and work
  out structure must generate function.
• Properties will emerge naturally
• Example Bouncing Ball
• X0, Y1000 Start at top left of world
• DX10, DY0 Ball is rolling right but not
  yet falling
• LOOP Every tick, do the following
• XXDX Add speed to last X, Y position
• YYDY to calculate balls new position
• DYDY-1 Vertical speed changes due to
  gravity
• IF Ylt0 THEN If we have hit the floor
• Y0 Dont bounce right through it!
• DXDX0.7 Include some friction to the ball
  in
• DYDY0.7 both the horizontal and vertical
  directions
• by multiplying the speed by a fraction
• DY0-DY Reverse the balls vertical
  direction
• END IF Thats the bounce dealt with

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Orders of simulation

• 1st order procedural space
• 2nd order parallel universe

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1st Order Structure

• Strives to be sufficiently realistic
• Brittle system attempts to simulate appearance
  error in 1st order magnifies in consecutive
  orders
• Robust system simulates global behavior despite
  differences in internal structure

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2nd Order Structure

• Arises from communication amongst 1st order
  building blocks
• Procedural space becomes a parallel universe

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Chapter 7 They Call Me Legion For I am Many
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Human Simulation

• Simulation as result of computer program
• 1st order atomic motion
• 2nd order life, conciousness, intelligence
• Data provided to the model determines the function

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Algorithms vs. Second-Order Structures

• Algorithm is single serial computation
• Second-order virtual machines can be put together
  to build organizations
• Machines do their own internal processing
• Machines communicate to produce parallel
  computation

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Parallel systems and time-slicing

• Time slicing is separation of test phase and
  change state using buffered storage
• A computer using a time-slicing loop is able to
  perform several functions and not be devoted to a
  single one

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Intelligence

• Intelligence is not the ability to follow rules
  it is the ability to develop rules in the first
  place.
• Intelligence is the result of billions of
  unintelligent processes operating concurrently.

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AI Research

• Programs are not intelligent because they only
  contain portions of stored intelligence
• AI research needs to be focused on
  pseudo-parallel algorithms

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Simultaneity

• Simultaneity is the key to intelligence in
  simulation
• Turning serial algorithms into parallel systems
  allows things to happen simultaneously

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• I do have a strong hunch that intelligence is
  necessarily parallel in nature and yet, as long
  as a computer program runs quickly enough in
  relation to the speed at which the outside world
  is changing, it is acceptable to simulate this
  parallelism by time-slicing on a serial computer.

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Chapter 8

• -Creatures stay in their ideal place in the
  environment through the magic of feedback loops
• Cybernetics the formal study of feedback systems
  
• -Feedback is an essential component of life and
  comes in two types
• 1. positive tends to intensify a change
• 2. negative tends to oppose a change,
  stabilizing the system

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• For example
• 1. A manager tells workers they are performing
  well on the job and the workers respond by
  performing even better.
• (Good work praise better work)
• 2. A manager reprimands workers for performing
  poorly and they respond, in frustration, by
  performing even poorer.
• (Bad work criticism worse work)
• Both are examples of positive feed back! The
  thing being fed back, the managers opinion,
  amplified a change in the workers behavior.
• Note What determines or is completely
  independent of the feedback itself
• In nature As the climate cools, animals growth a
  thicker fur coat

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• Negative feedback means the managers opinions
  counteract a change in the workers behavior
• 3. If the manager praises poor performance, and
  reprimands good performance, the work will
  stabilize in the middle
• (Bad work praise better work) and (Good work
  criticism worse work)
• Negative feedback in nature Animals are growing
  thicker fur coats, while the climate begins to
  warm

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• 4. If a worker knows that he/she is working
  poorly and is then praised, the worker will
  respond to the decreased demands with less
  effort.
• (Bad work praise worse work)
• This is an example of adaptation of the amount of
  effort by the worker.
• Adaptation is the first law of biology it is a
  common feature of biological systems that
  exploits feedback
• Looking at the system as a whole
• There are two feedback loops at work here.
• 1. On a longtime scale, negative feedback
  (Adaptation)
• 2. On a short timescale, positive or negative
  feedback (the managers opinion)

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Feedback loops can be compared to a feedback
landscape of hills and valleys where hills are
positive and valleys are negative feedback.
-Feedback landscapes are continually changing
in two ways 1. The population is evolving 2.
The environment is changing Life -it is a
journey along an uneven feedback
landscape -during the journey, there are limited
amounts of resources and energy available
-organisms must continually move forward along
the landscape as it crumbles behind them -the
challenge of life is to remain running on one of
the ridges without slipping beyond
recovery -intelligence is the ability to use past
experience of cause and effect to predict future
events, intelligence helps insure survival
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• Observer Effect
• Things in life have meaning relative to the
  observer because of their utility
• A statue has something a lump of clay does not
• A computer has something a slab of silicon does
  not
• This difference can best be described as
  elegance
• The environment, as an observer, selects
  phenotypes with the most utility
• This utility is relative to the environment
• In a cool climate, thick fur coats have a greater
  utility than thin coats. If the climate warms,
  thick coats will no longer have the greatest
  utility

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• Chapter 9
• The Building Blocks of Life
• One way to categorize these blocks it by their
  anatomical features
• -cells to tissues to organs
• -life can then be defined by its features
  (compositional definition)
• An organism can also be thought of as a network
  of feedback loops. Life can then be defined by
  its processes rather than its features
  (functional definition)
• By looking at the larger picture of the function
  of an organism, not simply the composition of its
  parts, we see that it is more than the sum of its
  parts
• The building blocks of life are not the physical
  anatomy but the informational layout.
• This type of building block can be implemented in
  a computer as first-order components

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Chapter 10 The Whole Iguana
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Upon watching his friend dismember a spider as a
child, Grand makes two observations regarding
life.

• Only through an organisms interactions with its
  own environment can intelligence truly become
  evident. It is the fight for survival that
  creates this basis and generates intelligent
  motives and actions.
• Intelligence is only possible as a whole. An
  organism is either whole or not an organism at
  all.

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Observation 1Only through an organisms
interactions with its own environment can
intelligence truly become evident. It is the
fight for survival that creates this basis and
generates intelligent motives and actions.

• Example
• With its limbs removed, the spider continues to
  try and use its removed appendages to continue
  moving.
• An organism must receive feedback from its
  environment in order to learn.
• Lack of interaction with its environment creates
  a void where intelligence should reside.

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• Intelligence without action is not even
  achievable.

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• It is possible for organisms, most notably human
  beings, to express intelligence by using their
  imaginations.

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An organisms survival plays a key roll in
demonstrating intelligence.

• Example
• If you ask an individual an intellectually
  stimulating question, what is the purpose or
  reasoning the person would give for answering?

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This brings us to the concept of Artificial
Intelligence.

• How do we construct an intellectual entity on
  these guidelines of survival?

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What does Grand suggest?

• Supply a reward or punishment to the system
  artificially!

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Example

• Grand uses the example of people associating a
  stern look with being physically hit or spanked
  when we were younger by a displeased adult.

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Observation 2Intelligence is only possible as
a whole. An organism is either whole or not an
organism at all.

• As a general rule, if you take an organism to
  pieces you do not end up with pieces of an
  organism. All you get is a sticky mess of
  lifeless bits of meat or vegetable matter.

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Example

• How far much of a humans brain can you remove
  until they are no longer considered a human?

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This example leads us directly to the critical
thinking question asked by Grand.

• So why do so many who attempt to create thinking
  machines expect to be able to implement just one
  specific aspect of intelligence and get away with
  it?

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Example

• An adult runs into the middle of a busy road in
  order to prevent a child from getting hit by a
  bus.
• Why should this be considered intelligence?

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In order to create a complete system we can
correctly term Artificial Intelligence Grand
gives five required components.

• 1) A brain capable of learning and acting as a
  result of prior interactions within a realistic
  environment.
• 2) An emotional system which allows for rewards
  and reprimands to motivate action.

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• 3) An ability to eat and continue living in order
  to associate its intelligence with survival.
• 4) An ability to speak and communicate (mostly to
  communicate with its owner).
• 5) An ability to find a mate and reproduce an
  offspring which shares the genetic background
  of its parents.