Alternative theories S2W6

Question 1

motor programs

Answer 1

An abstract representation, that when initiated results in the production of a coordinated movement sequence. (Schmidt)

Question 2

generalised motor programs (GMP)

Answer 2

A motor program whose expression can be varied depending on the choice of certain parameters. (Schmidt)

Question 3

motor programs in a perfect world

Answer 3

• in a perfect world, motor programs give the exact same output each time
• perfectly executable and repeatable
• perfect control
• a set of instructions that are carried out in the same way to give the same result - tells you what to do

Question 4

not motor programs

Answer 4

• If you assume you have evolved to work in a noisy (less than perfect) environment, then maybe you can have a system that is designed to work within this, rather than it trying to be perfect and failing
• So every system has noise so need to cope with it and maybe have different ways of functioning that take it into account instead of fighting it
• Might have to settle for “good enough”
• “good enough” = not a failure, still doing task, but might has some noise or error to it
• Turns out that lots of things that look like noise that are not, they are just complex
• If it is a complex pattern that is happening rather than it just being noise, you need tools to be able to measure and analyse it to see it, otherwise just looks like a mess
• This requires different approaches and ideas

Question 5

mean and standard deviation don’t tell the whole story

Answer 5

• graphs for same data with same mean and SD could look different due to different movement patterns
• need measures which take into account how the signal changes or develops over time
• there are various ways it can be done, all more complex than getting mean and SD as more information needed to understand what’s happening

Question 6

measuring the right thing (think street map example)

Answer 6

• Before deciding what tools you need to use, find out what you need to measure in the first place
• Diagonal will only be shorted if a it’s a single diagonal line
• Diagonal line is a 1D solution
• x + y is a 2D solution
• Diagonal with some x + y = fractional dimension (something between 1D and 2D)
• 2D distance = x + y
• 1D formula = square root of (x^2 + y^2)
• Fractal = somewhere in between 1D and 2D

Question 7

dynamical system

Answer 7

• A system that changes and evolves with time

- Isn’t easy to figure out what’s going on

Question 8

chaos

Answer 8

• Events might seem random but are defined by rules and scientific laws
• Not easy to predict

Question 9

complex systems

Answer 9

• e.g. differential equations

- there’s a pattern to it

Question 10

emergence

Answer 10

• Get an overall pattern when lots of little things interact
• Everything in it can be dumb but you still get something that looks smart at the end of the day
• Lots of things interacting but suddenly they behave like one organism
• E.g. if you dump a pile of sand it will emerge into a cone shape

Question 11

chaos theory (non-linear dynamics)

Answer 11

• complex non-describable things can have simple underlying rules, so can be understood even if not predicted
• Newton’s Laws suggest everything that happens can be explained by these rules
• Poincare (French mathematician) used Newton’s Laws to predict whether solar system would stay stable or not - he found that he couldn’t predict as the solar system obeys Newton’s Laws but after a while, small perturbations grow and random effects can occur
• complex systems - lots of things interacting closely
• e.g. bird flocking - each starling responds to the air currents and visual cues from starlings close to them
• combination of this produces coherent patterns called emergent behaviour - lots of things interacting but they behave like one big organism
• e.g. earthquakes - can’t predict them but they’re not completely random, there are events leading to them

Question 12

constraints

Answer 12

• Instead of deciding you will have to have an outcome, you restrict other things
• E.g. walking - can decide exactly how to walk - constraint is not to fall over - trying to do ‘good enough’ things to give a proper outcome

Question 13

the difficulty of predicting the future and why is this a good thing

Answer 13

• Not being able to predict what your system is doing in the future is the non-linear, noisy world we live in
• This is good for sports, or it would be very boring (and bad for the bookies)
• BUT
• totally rule-bound, error free systems exist (no human or environmental error, but predicting the future is still difficult)
• predicting the future can still be futile (difficult) when decisions are made over time (as opposed to planned from the outset)
• when decisions are made over time

Question 14

games with endless combinations like chess

Answer 14

• 1st round of chess there are 20 possible moves each - 400 options
• by the 5th round there have been a trillion options
• no noise in this but still can’t plan for every opportunity
• can use strategies, groupings, principles, patterns
• even fully constrained systems can become so complicated you can’t work them out
• in the real world there is noise as well and not as clear rules