2d:null 2e:["$","title",null,{"children":"Assignment #3 | KarlieDoesNotExist | Observable"}] 33:Tb50,md` ## Article Response of Valentino Braitenberg's **Vehicles: Experiments in Synthetic Psychology**

The article gives an in-depth analysis of synthetic psychology - understanding behaviour through robotics. By sequentially adding extra motor-sensor connections, we obtain "vehicles" that get changes in their movement each time and finally with complicated mammalian-like behaviours. Meanwhile, it's a point that can be perfectly connected to the idea of agencies in computational art. It's important, though, to keep in mind that this behaviour is goal-directed, flexible and adaptive, and even appear to be intelligent, yet, the functioning of the agent is **purely mechanical**, without any **information processing** or other apparently **cognitive processes**. Back to generative art, "agency" can be considered as a type of artificial intelligence, although compared with deep learning and neural networks it now seems to be a rather simple one. We've seen a lot of artists using agencies (particles with special rules) to create graphics. To me, the speciality of agencies seems to be its self-organisation. When we are utilising these agencies as a medium to produce art, the medium is not fully controlled by the artist anymore. But differs from "randomness" in computational art, these agencies seem to be alive, intelligent and organised, imitating mammal movements in a relatively shallow level.
Thinking about it in the way of neuro science:
Sensor - Motor => Stimulation - Response
1st level - "monotonic movement"
"the more, the more/less"
2nd level - Fear and Aggression
the speed varies with the distance - a non-linear dependence of the speed (of certain motor) on the intensity of stimulation (motor - sensor)
3rd level - limits/Friction (the author calls it "love" but I'm not sure if it's appropriate)
friction & threshold of activation Complex networks of these "neuro pairs"
4th level - inhibitory
counteract the activation that comes from other sources
5th level - Logic (numbers)
Clusters, interactions between groups and individuals
6th level - Memory
Repository that remember (part of) the trail of the vehicle
7th level - Selection & Darwinian Evolution
computational => biological evolution
the introduction of error; generation and iteration

"Law of uphill analysis and downhill invention", as another way of saying "analysis is much more difficult than synthesis"
"It is much more difficult to start from the outside and to try to guess internal structure just from the observation of behaviour. It is actually impossible in theory to determine exactly what the hidden mechanism is without opening the box, since there are always many different mechanisms with identical behaviour. "

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