Dobyns, J.; Johnson-Shelton, N. & Rometsch, M.: Falscher Engel: Mein Höllentrip als Undercover-Agent bei den Hells Angels. Ullstein Taschenbuch, 2011

»Falscher Engel« ist die faszinierende Geschichte eines außergewöhnlichen Mannes, der sich in die verbotene und lebensgefährliche Unterwelt der eingeschworenen Hells-Angels-Gemeinschaft einschleust. Zwei Jahre lang arbeitet Jay Dobins in dieser berühmt-berüchtigten südwestamerikanischen Rockergang als verdeckter Ermittler.
In dieser Zeit führt er das mörderisch spannende Leben eines muskulösen, tätowierten und bis an die Zähne bewaffneten Raubtiers auf einer dröhnenden Harley, inmitten eines Rudels gefallener Engel. Doch dieses Doppelleben führt Dobins an den Rand seiner eigenen Existenz und hinterlässt tiefe Spuren auf seiner Seele. Als Zeuge zahlreicher (Kapital-)Verbrechen, gefangen im Strudel der Ereignisse und beeinflusst von charismatischen Personen verliert er fast den Halt. Um ein Haar wäre er der Aura der Höllenengel und der Besessenheit des Bösen erlegen. Und hätte dabei seine Familie, seine Gesundheit und letztendlich sein Leben in der Hölle aus Lügen, Drogen und Gewalt zurückgelassen …

Montaner, M.; López, B. & de la Rosa, J. L.: A Taxonomy of Recommender Agents on the Internet. In: Artificial Intelligence Review 19 (2003), Nr. 4, S. 285-330
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Recently, Artificial Intelligence techniques have proved useful inhelping users to handle the large amount of information on the Internet.The idea of personalized search engines, intelligent software agents,and recommender systems has been widely accepted among users who requireassistance in searching, sorting, classifying, filtering and sharingthis vast quantity of information. In this paper, we present astate-of-the-art taxonomy of intelligent recommender agents on theInternet. We have analyzed 37 different systems and their references andhave sorted them into a list of 8 basic dimensions. These dimensions arethen used to establish a taxonomy under which the systems analyzed areclassified. Finally, we conclude this paper with a cross-dimensionalanalysis with the aim of providing a starting point for researchers toconstruct their own recommender system.

Yu, B. & Singh, M. P.: Searching social networks. Proceedings of the second international joint conference on Autonomous agents and multiagent systems. New York, NY, USA: ACM, 2003, S. 65-72
[Volltext]
A referral system is a multiagent system whose member agents are capable of giving and following referrals. The specific cases of interest arise where each agent has a user. The agents cooperate by giving and taking referrals so each can better help its user locate relevant information. This use of referrals mimics human interactions and can potentially lead to greater effectiveness and efficiency than in single-agent systems.Existing approaches consider what referrals may be given and treat the referring process simply as path search in a static graph. By contrast, the present approach understands referrals as arising in and influencing dynamic social networks, where the agents act autonomously based on local knowledge. This paper studies strategies using which agents may search dynamic social networks. It evaluates the proposed approach empirically for a community of AI scientists (partially derived from bibliographic data). Further, it presents a prototype system that assists users in finding other users in practical social networks.

Parent, S.; Mobasher, B. & Lytinen, S.: An Adaptive Agent for Web Exploration Based of Concept Hierarchies. Proceedings of the 9th International
Conference on Human Computer Interaction. New Orleans, LA: 2001
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Steels, L.: The Origins of Ontologies and Communication Conventions in Multi-Agent Systems. In: Autonomous Agents and Multi-Agent Systems 1 (1998), Nr. 2, S. 169-194
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