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This special issue is the result of the selection and re-submission of advanced and revised versions of papers from the workshop on "e;Trust in Agent Societies"e; (11th edition), held in Estoril (Portugal) on May 10, 2008 as part of the Autonomous Agents and Multi-Agent Systems 2008 Conference (AAMAS 2008), and organized by Rino Falcone, Suzanne Barber, Jordi Sabater-Mir, and Munindar Singh. The aim of the workshop was to bring together researchers from different fields (artificial intelligence, multi-agent systems, cognitive science, game theory, and social and organizational sciences) that could contribute to a better understanding of trust and reputation in agent societies. The workshop scope included theoretical results as well their applications in human-computer interaction and electronic commerce. It was constituted by a main session integrated with two others: the first on the formal models of trust, and the second on reputation models. In this volume we present papers from the three workshop sessions: the main s- sion with papers on theoretical and applicative aspects of trust (from a engineering, cognitive, computational, sociological point of view); the formal model session with works in the field of applied logic and applied mathematics; the reputation models session with papers that specifically address models of reputation systems, theo- driven and empirically backed-up guidelines for designing reputation technologies, and analysis and discussion of existing reputation systems.
Autonomy is a characterizing notion of agents, and intuitively it is rather unambiguous. The quality of autonomy is recognized when it is perceived or experienced, yet it is difficult to limit autonomy in a definition. The desire to build agents that exhibit a satisfactory quality of autonomy includes agents that have a long life, are highly independent, can harmonize their goals and actions with humans and other agents, and are generally socially adept. Agent Autonomy is a collection of papers from leading international researchers that approximate human intuition, dispel false attributions, and point the way to scholarly thinking about autonomy. A wide array of issues about sharing control and initiative between humans and machines, as well as issues about peer level agent interaction, are addressed.
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