Before we start with the description of behaviour-based systems, we will set a
background in artificial intelligence, of how, why, and from where is that behaviour-based
systems come from. We also address some problems present in artificial intelligence, such as
the concept of intelligence, and the capabilities of intelligent machines. Then we describe
behaviour-based systems. Finally, we mention some of the applications of behaviour-based
systems.
1.1. Background
“The hardest thing to understand is why we can understand anything at all”
—Albert Einstein
From the beginnings of Artificial Intelligence (AI), in the late 1950's, researchers in the
area have tried to simulate human intelligence by representing knowledge. Knowledge
representation is among the most abstract ways of exhibiting intelligence. It is also among the
most evolved ways of exhibiting intelligence. This is, animals less evolved than humans might
exhibit intelligence, but not at a knowledge level3. This has lead researchers simulating
intelligence to create the so called knowledge-based systems (KBS). Thus, KBS are tailored for
the simulation of the most abstract elements of thought (reasoning, for example). This has lead
KBS to be very effective in simulating abstract ways of exhibiting intelligence, by successfully
demonstrating theorems, solving problems, playing chess, etc. Essentially, simulating things
which were “very difficult”, from an intellectual point of view. KBS were good at where the
people who gave the knowledge to build the KBS were good at. But it came that it was very
difficult for KBS to simulate successfully “very simple” things, also from an intellectual point
of view; activities such as walking in crowded corridors, cleaning, parking a car, etc. Basically,
things we do subconsciously, without any intellectual effort, but require a lot of coordination,
and complex interaction with an open environment. It was clear that modelling “simple”
intelligence from “abstract” intelligence was neither easy, nor computationally efficient.
So, by the middle 1980's, researchers in AI realized that the “simple” intelligence they
were trying to model was present in animals, in their adaptive behaviour (McFarland,1981;
Beer, 1990; Pfeifer and Scheier, 1999), which is studied by ethology (Manning, 1979; Tinbergen,
1951; Lorenz, 1981). Animals perhaps cannot play chess successfully (Brooks, 1990), but it
seems that it is very easy for them to search for food if they are hungry, organize in societies if
they need it, run away if they perceive a predator, etc. In general, animals can react, and adapt,
to the changes in their dynamic environment. This behaviour, for an observer, appears to be
3Recent studies show that animals are capable of exhibiting simple forms of knowledge (e.g. congo parrots
(Pepperberg, 1991)), but these issues were not considered by AI researchers in the middle of the twentieth
century.