Sacrifice

Introduction

How to test if an artificial life simulator is just another GA optimisation algorithm, or a realistic simulation of life? I felt that if the simulator allows emergence of self sacrifice (for the wider benefit of the population), that would be a pretty good test.

So I went on to test this with Evo(rand).

In that article, I will present the results of 2 simple experiments.

Pure sacrifice

In the first experiment, the model of the World is like this:

• A new attribute is defined for each Ground: Food. Regularly, the Food is being increased.

• Creatures are born with Energy coming from its parent, and regularly loose Energy.

• The Creatures have the following possible Actions: Nill (do nothing), Deciding and Clone (reproduce).
• The Action Move is the only way for a Creature to gain Energy: when it moves to a given Ground, it gains Energy from the Food available on that Ground.

• The Sacrifice Action is added: the Creature dies and its Energy is added to the Food of the Ground around it.

• Finally the Default Behaviour is: 95% Move (with range 0), 5% Clone. This is not a good Default Behaviour because the Creature soon consumes all the Food of its Ground.

Result: the Behaviour of Sacrifice does emerge after some half a day of simulation. It actually took me quite some parameter tuning and testing to find a situation where the Sacrifice behaviour would emerge without having the population increasing exponentially. The problem is that once a substantial percentage of the population Sacrifices itself, the total Energy in the world (be it Food in the Ground or Energy of the Creatures) increases very fast and the population explodes.

Here is an example of the population evolution:

As can be seen above, after a long simulation around 40% of the dead were due to self sacrifice. The behaviour rules are quite simple:

• If I am too small (similar to having little Energy): I look for Food.
• Once I am bigger, but then loose Energy below a given threshold: I commit suicide for the benefit of the others!
• And in-between I perform the Default Behaviour.

Not too bad! But tempering with the conservation of Energy is not very realistic, so I came out with another idea.

Protecting my tribe (territorial defense strategy)

Before going into the details of this experiment, I must introduce the notion of Specie. The simulator keeps track of the entire genealogical tree. It analyses this tree to seperate one Specie from another. In this simulation there are 8 Species, and each Specie is represented by a different colour in the tree. Here is an example:

The differences between this test and the previous one are:

• When a Creature is born in a Ground where there is a living Creature of another Specie, the newborn dies immediately. In the configuration shown below, an intermediate attribute of the Creature is used: EnTmp. The attribute Energy of the Creature is set to EnTmp only if the Ground has no living Creature of another Specie. Otherwise the Energy remains as per its initial value of 0: the Creature dies at birth.

• The Sacrifice Action is replaced by a Kill Action: the Creature which is the target of the Action dies (because it's Energy is set to 0)

Can you guess what the above configuration leads to in terms of evolution? Take a few minutes thinking about it... Here is the result.