maximize the pleasure-function which is defined on the space of ideas. We recall that the interest-measure increases with the decreasing of the distance from an idea-attractor to the interest-database.

We now consider Model 3. Here a brain can calculate not only the interest-function on the space of ideas, but also the interdiction function. The purpose of the latter one is to prevent such a brain from conflicts with reality. Here we chose a pleasure-reality function is identified with the consistency-function. As was mentioned, the simplest form of the consistency function is simply the difference between the functions of interest and interdiction:

## Pleasure—Reality = Interest - Interdiction,

Thus the greatest pleasure and at the same time the greatest consistency with reality is approached in the case of the highest interest and the lowest interdiction, e.g., the interest-measure = 1 and the interdiction-measure = k , so the the pleasure-reality function takes the value 1-k. It is a good point to remark that the pleasure-reality function (given by the measure of consistency) depends on an individual. In general it is an arbitrary linear combination of interest and interdiction:
PLEASURE—REALITY = a INTEREST + b INTERDICTION,

## Where A And B Some Coefficients.

In Model 4 the pleasure-reality function is the same as in Model 3. Finally, we consider Model 1. Here we have only dynamical systems which process external and internal stimuli and produce ideas-attractors which play the role of reactions to those stimuli. Pleasure is approached by realizations of those ideas-attractors. Here Id totally dominates. We now analyze deeper the structure of the pleasure function. As everything in our models this function is based on the mental distance. Therefore the pleasure principle as well as the reality principle are based on the metric structure of mental space.

## 3 4 	 - 	

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We do not plan to present here a detailed review on other approaches to psycho-robots. To emphasize differences of our approach from other developments of psycho-robots, we present a citation from the work of Potkonjak el al, 2002:
"Man–machine communication had been recognized a long time ago as a significant issue in the implementation of automation. It influences the machine effectiveness through direct costs for operator training and through more or less comfortable working conditions. The solution for the increased effectiveness might be found in user-friendly human–machine interface. In robotics, the question of communication and its user-friendliness is becoming even more significant. It is no longer satisfactory that a communication can be called "human–machine interface", since one must see robots as future collaborators, service workers, and probably personal helpers." In contrast, the main aim of our modeling is not at all creation of friendly helpers to increase their effectiveness. We would like to create AI-systems which would really have essential elements of human psyche. We shown that already psycho-robots with a rather simple AI-psyche - two emotions and two corresponding data bases
- would exhibit (if one really wants to simulate human's psyche) very complicated psychological behavior. In particular, they would create various psychical complexes which would be exhibited via symptoms. We also point out to the crucial difference of our "Freudian psycho-robots" from psycho-robots created for different computer game ("psycho-automata").

Our aims are similar of those formulated for humanoid robots, see e.g. Brooks et al., 1981a,b, 1999, 2002. However, we jump directly to high level psyche (without to create e.g. the visual representation of reality). The idea of Luc Steels to create a robot culture via societies of self-educating robots, Manuel, 2003, is also very attractive for us. It is clear that real humanoid psyche (including complexes and symptoms) could be created only in society of interacting Psychots and people. Moreover, such AI-societies of Psychots can be used for modeling psychoanalytic problems and development of new methodologies of treatment of such problems.

## 5 ,

We proposed a series of the AI-type models for advanced psychological behavior. Our approach is based on geometrization of psychological processes via introduction of mental metric space, dynamical processing of mental states and emotional-type decision making based on quantative measures of interest and interdiction and corresponding data bases of ideas. Increasing complexity of AI-modeling implies with necessity appearance of psychological features such as complexes and symptoms which are being handled by psychoanalysis during the last hundred years. Such a