The Comparison between Social Learning and Individual Learning: an Approach Based on Genetic Programming

Multiagent system research tries to obtain predictability of social systems whilst preserving autonomy at the level of the individual agents. In this paper, social theory is called upon to propose a solution to this version of the micromacro problem. The use of norms and learning of norms is one possible solution. An implementation of norms and normative learning is proposed and evaluated using simulation studies and measures for the internalizing and spreading of norms. The results of the simulations provide food for thought and further research. Modeling the norm set of the group in accordance with the individual mindset in absence of other information (i.e., at the beginning of the group-forming process) proves to be a more fruitful starting point than a random set. INTRODUCTION Multiagent system designers face the problem of how to ensure efficiency at the level of the multiagent system whilst respecting individual autonomy. This is in a sense the inverse of the problem of sociology, which tries to explain how social cohesion is possible in a world where individuals become more autonomous. Multiagent system development is like social engineering, with a focus on the reduction of behavior variance whilst maintaining the agent’s autonomy. In this sense, multiagent systems research is focused on solutions to the micro-macro problem. I will discuss some theories from the social sciences that may help multiagent systems research in balancing individual autonomy and system efficiency. Issues of autonomy will not be discussed; for these, the reader is referred to previous writings, e.g., Verhagen (2000). One possible solution to the problem of combining social level efficiency with autonomous agents is the use of central control (thus limiting the individual’s autonomy severely). In human social systems such as organizations this is realized via bureaucracy. In multiagent systems it is the central coordinator that plays this role. This solution works only when the social system’s environment has a low rate of change (including changes in the set of individuals included in the social system) since central control has as one of its main characteristics a low rate of adaptability (see Carley and Gasser [2000] for a discussion on the impossibility of an optimal organizational structure). When flexibility is of the essence, other solutions are called for. An intermediate solution is internalized control, e.g., the use of social laws (Shoham and Tennenholtz 1992). Structural coordination as proposed in Ossowski (1999) is another example of an intermediate solution that is only suitable for closed systems (or at least systems in which the behavior of new members has to conform to preconceived rules). Open * Corresponding author address: Harko Verhagen, Electrum 230, SE-16440 Kista, Sweden; e-mail: [email protected]; http://www.dsv.su.se/~verhagen/welcome.html.