"There is nothing as practical as a good theory."
- Kurt Lewin
Traditional behavioral sciences positivistic paradigm based on experiments and empirism is sub-optimal since it reveals only descriptive causal relations. The goal of computational psychology is to develop mathematical models to advance the behavioral sciences. When simulated with computer these models describe the cognitive processes of individuals. Computational psychology is all about building psychologically plausible mathematical models, which incorporate all the current knowledge and thus describe cognitive processes instead of simple causalities or correlations.
There has been some research carried out by physicists such as Tamas Vicsek, who has simulated the features of the escape panic and studied the synchronization of applause in a concert hall. Another example the physicists' efforts to study of social networks lead by Albert Laszlo-Barabasi. These studies are interesting and valuable examples of applying methods of physics to collective phenomena. However, the challenge is that human phenomena is treated as statistically with the methodology of statistical physics and all the existing psychological knowledge is ignored in these studies and replace with adhoc common sense solutions. In this way one cannot really understand, interpret or explain of social phenomena, which are the goals of social science. For understanding simple modeling of action does not help - we must study the causes of action. The ability to interpret, explain and understand human behavior comes from understanding and modeling the underlying cognitive processes.
The field theory
In the 1930's one of the most eminent psychologist of all time Kurt Lewin published the books Principles of topological psychology (1936) and The conceptual representation and the measurement of psychological forces (1938). In the latter book he presented his field theory, which states that human behavior is determined by goal-directed psychological forces in a topological space as the function of both the person and the environment: B=f(P,E). This was ground-breaking since most of the psychology at the time was carried out by behaviorists. The scientific community did not adopt the paradigm then and after the second world war the rise of postmodernism and social constructionism overrode Lewin's subtle ideas, which required a lot of mathematical rigor not typical for psychologists neither then nor now.
Stochastic theory of social interaction
The first Finnish professor of social psychology Kullervo Rainio has corrected some deficiencies in Lewin's assumptions and revised the field theory to stochastic theory of social interaction. The theory can be found summarized in the book Cognitive process and behavior - conceptual framework and simulations. In Rainio's theory, the cognitive states are vertices of a graph and the change of the cognitive state is determined by transition probabilities (which vary based on previous behavior, learning or interaction). The decision to take action is made based on the present cognitive state and the action is never deterministic. This process can be easily simulated in discrete time and Rainio has shown that it estimates simple behavior in laboratory circumstances quite well. However, theoretical psychology still remains outside the mainstream behavioral and psychological scientific community, perhaps even more so than before.
I think that both Lewin and Rainio have made pioneering work in developing theoretical social psychology as a counterbalance to theoretical physics. The problem is that those, who are interested in psychology cannot typically calculate much without SPSS and thus there is a threat that these complex mathematical theories requiring knowledge about graph theory, stochastic processes and group theory may be forgotten soon. One should note that Lewin's and Rainio's theories are holistic, i.e., the human being is seen as a whole, whereas modern psychology is specializing more and more (e.g. neuropsychology).
I am interested in developing the holistic theory of human behavior further with methods of physics and mathematics, however, without forgetting the essential psychological framework. I am going to suggest a new methodological paradigm for behavioral science and establish a conceptual and mathematical framework for methodological and theoretical development of computational psychology. In additon, I will show how many well-known psychological theories can be exploited computational modeling of individual and group phenomena. These computational studies have applications ranging from epidemological prediction to business strategy.