Equipped with these considerations we will now start to explore the space of possible structures. For this we define some 'guidelines' which we will follow in search of possible solutions.

Thus we will have in any concrete case at least a 3-tupel $ \langle th, MEAS, EXP\rangle$ telling us, which experiment $ EXP$ has been used to test which kind of a model $ th$ (as instance of a theory $ TH$) with which kinds of measurement. This leads us to a 3-dimensional matrix as the space of our investigations.

Example: The triple $ \langle Random, Steps-Energy, Wood1\rangle$ could be a representation of the configuration: $ Random$ is a completely random agent as instance of a theory of random input-output systems; $ Steps-Energy$ are methods measuring the number of steps to reach a defined goal in this environment and/ or the amount of energy consumed.$ Wood1$ is the 'wood1' environment as described in the paper of Wilson (1994) [422].

The following list is a 'dynamic' list which will grow through time. The list will not include the subject of genetic algorithms because these are following other guidelines2.12. Furthermore is this table without any details. For all agents we assume a 'built-in' fitness function using at least one 'drive'. The overall fitness function is part of the environment and is not visible to the system.

Roadmap for IESS      
Random time [T], energy [E] Wood1 Plus-Labyrinth      
Reactive [T],[E] Wood1 Plus-Labyrinth      
Learning Classifier [T],[E] Wood1 Plus-Labyrinth      
Memory L1 [T],[E] ] Wood1 Plus-Labyrinth      
Memory L1-L2 [T],[E] Wood1 Plus-Labyrinth      
Memory L1-L3 [T],[E] Wood1 Plus-Labyrinth      
Memory L1-L3, signs [T],[E] Wood1 Plus-Labyrinth      


For the final implementation of the preceding theoretical considerations we follow the outline of figure 2.7 and we will set up a simulation framework according to figure 2.10. All mentioned modules are communicating by sockets (or equivalent devices). On account of the hight mathematical maturity of the scilab software we will use scilab for the main modules. What will be described below represents a 'start configuration' with a 'machinery' as simple as possible.

Figure 2.10: Simulation Framework for the Engineering of Intelligent Evolutionary Semiotic Systems

Gerd Doeben-Henisch 2013-01-14