We believe that, in order to model plausibly reasoned behaviour in an open,
unpredicted, non deterministic environment, we should model first convincingly reflex, reactive,
and motivated behaviours. Reasoned behaviours need the other behaviours, not only because
reason (and higher cognition) evolved from adaptive behaviour, but because we can distinguish
a hierarchy among the types of behaviours described above. For example, if I am in a night club,
hierarchically, first, I will breathe to stay alive (vegetative); then, I will move my foot if someone
steps on it (reflex); then, I will probably clap if everyone begins to clap (reactive); then, I will
ask a girl for a dance if I feel attracted to her (motivated); then, I will begin to think about what
to speak with her (reasoned); and finally, I will ask myself what am I doing in such a place
(conscious). We can see that the less complex types of behaviours will dominate the more
complex, not only because the execution of the more complex behaviours (in most cases) does
not prevent the execution of the less complex (I can keep breathing while moving my foot, I can
reflexively move my foot while clapping and dancing, etc.), but also because the more complex
types of behaviours need of the execution of the less complex in order to be executed (I need
to breathe to live, I need to move my foot to dance, I need to like a girl to think how to seduce
her, and I need to have all the previous experiences in order to be aware of them and rethink
what I am doing). Also, the low plasticity in the less evolved behaviours makes them hard to
control by the more evolved. For example, we can control hunger (motivated) with reason more
or less successfully, but it is harder to control our dance steps (reactive) in a different way than
we are used to, and it is very hard indeed not to scream if some part of us is burning (reflex).
Behaviours that took generations to be learned by evolution are harder to forget than
behaviours learned in one day.
Each type of behaviour solves a problem. The next behaviour was evolved over the
previous without losing the capability of solving previous problems. We believe we should
engineer our artificial systems in the same manner: build a subsystem to solve a problem. Then
build over the previous subsystem another one to solve a new problem, but without losing the
capabilities of solving the first problem(s), in a bottom-up fashion. By following the steps of
natural evolution, we can simulate more completely creatures created by it.
Before being humans, we are animals. If we want to simulate human reasoning, we need
to simulate properly animal behaviour. Also, we would need a culture, a language, and a society
to obtain reasoned behaviour from adaptive behaviour.
In the present work, we join the effort of the community to model adaptive behaviour,
in order to set a behavioural basis of cognition. We do this by engineering artificial societies of
intelligent agents, to understand intelligence emerging from adaptive behaviour, building
artificial societies on the way.