Socionics: Scalability of Complex Social Systems (Lecture Notes in Computer Science, 3413)

1 Thisbookis an outcomeof the SocionicsResearch Framework. Therootsof Socionics lie in the 1980s when computer scientists in search of new methods and techniques of distributed and coordinated problem-solving ?rst began to take an engineering interest in sociological concepts and theories. Just as biological phenomenaare conceived of as a source of inspiration for new technologies in the new research ?eld of bionics, c- puter scientists working in Distributed Arti?cial Intelligence (DAI) became interested in exploiting phenomena from the social world in order to construct Multiagent S- tems (MAS) and, generally, to build open agent societies or complex arti?cial social systems. Socionics is driven by the underlying assumption that there is an inherent parallel betweenthe'up-scaling'ofMASandthe'micro-macrolink'insociology. Accordingly, one of the fundamental challenges of Socionics is to build large-scale multiagent s- tems which are capable of managing 'societies of autonomous computational agents . . . in large open information environments' ([9, p. 112]). As more sophisticated inter- tions become common in open MAS, the demand to design reliable mechanisms co- dinating large-scale networks of intelligent agents grows. Suitable design mechanisms may enhance the developement of 'truly open and fully scalable multiagent systems, across domains, with agents capable of learning appropriate communications pro- cols upon entry to a system, and with protocols emerging and evolving through actual agent interactions' ([10, pp. 3]) which is considered as the ultimate goal in ful?lling the roadmap of agent technology.