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Task 9 Collective intelligence (stuff to know (Turing machine --> if…
Task 9 Collective intelligence
stuff to know
Turing machine
--> if input then certain output
--> connected to chinese room
--> connect chinese room to drone/swarm intelligence (parts of the swarm might not be aware or understand waht he or she does within the swarm )
drivereinforment theory (by klopp)
--> look it up !!
swarm charachteristics (whole new way of thinking about business)
--> always go for global minimum ( highest efficiency)
why is swarm better?
flexebility, robustness , selforganisation
Can get stuck though cause they always take the most traveled way (the one with more pherhormone layers)
--> this way/trail must not be the most efficient one, just the one one ant traveled and accidentally found hte closest food
--> but this route might go in a big curve to the food even though a straight (but never traveled way) migh tbe faster
---> link it to creativity and being stuck on an oasis (place with no connection to better solution) :D !!
--> link with ACT R cause it always follows step by step to the next best tule to be executed, if stuck on oasis it could progress here and there but never reach goal cause no connection in problem space that would lead to GOAL seeked cause the creative space (oasis) is not connected to the big patch :D!!
anneling
heating up iron so it becomes mallable
--> if heated up (low arousal)= easy to form into new shape if not yet statsfied with it
vs
if cool (low arousal)= iron is very hard to form and shape and hammer into a form you would like (could get stuck in local minimum)
cool / low arousal stuck in local minimum = oasis
#
first high temp/ arousal to get new ideas
--> then low temp condition to make sense of the new ideas / "shapes" created by heating it up
--> then high condition again to shape it until perfection / get more ideas / influences
--> then cool again to make more sense of it or perfec tthe shape of the necklace :D !!
fish article = super importnat :D !!
decision making network --> called social behavior network (SBM)
works on decision rules :D!
fish use hillclimbing strategy
--> next best decision based on current state (no endgoal in mind)
--> so iif they observe another ish being more sucesfu than other fish they wil imitate that fish
// connections //
--> connection means end analyiss (where you have a goal in mind and plan each step up the hill based on the goal you want to achieve)
--> connection to backtracking (if impas reached based on decision made , backtrack to last state in which you hadoption to choose a different path/decision )
---> backtrackign and hillclimbin go hand in hand :3 !!
following leaders better fo ridiosynchratic decision
following swarm = better for repeated decisions (swarm learning of accident prevention o tesla cars :D !!)
quick Early gene expression in neurons after observing other fish
--> quick adaptation !!
Mesolimbic pathway
emotional assesment + memory
--> (like amygdala and hipocampus in humans
some things are differn in fish brain form human bran but similar enough to generalize
traveling salesman problem (connecting dots with ants :3 !!)
----> google traveling salesman problem AND ants
Agent based model (ABM)
different agents
4 rules
-->
-->
--> autonomy
--> population