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By Tina Balke, Frank Dignum, M. Birna van Riemsdijk, Amit K. Chopra (eds.)

This publication constitutes the completely refereed complaints of the ninth overseas Workshops on Coordination, companies, associations and Norms in Agent platforms, COIN 2013. The workshops have been co-located with AAMAS 2013, held in St. Paul, MN, united states in might 2013, and with PRIMA 2013, held in Dunedin, New Zealand, in December 2013. The 18 complete papers have been rigorously reviewed and chosen from 28 submissions and are provided including invited papers. The papers are geared up in topical sections resembling coordination, businesses, associations, norms, norm clash, and norm-aware agents.

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Extra info for Coordination, Organizations, Institutions, and Norms in Agent Systems IX: COIN 2013 International Workshops, COIN@AAMAS, St. Paul, MN, USA, May 6, 2013, COIN@PRIMA, Dunedin, New Zealand, December 3, 2013, Revised Selected Papers

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The methodology employed in the construction of the dolce ontology is the following. Firstly, we define basic properties and relations, that are generic enough so to be common to all specific domains, like being an endurant (more simply, an object), being a perdurant (an event), being a quality or being an abstract (entity), one entity being part of another, an object participating to an event or having a certain quality. . Then, we specify different modules, like the mental or the social module, that are composed by entities that share some characterizing features.

Thus, in order to design systems that are capable of assisting human agents in organizing and managing socio-technical systems, we need fine grained tools to handle several types of information. The aim of this paper is to discuss a general framework to describe socio-technical systems as cases of complex multiagent systems. In particular, we use a foundational ontology to address the problems of interoperability and conceptual analysis, we discuss how to interface conceptual information with low level information obtained by computer vision or perception, and we discuss how to integrate information coming from heterogeneous agents.

Technologically dense contexts, such as, for instance, airports, hospitals, schools, public offices [9]. The process of seeing a scene, forming a belief or an expectation and engaging in interaction with other agents are essential features of agents’ (both human and artificial) behavior in such systems. g. individual vs collective, visual vs inferential, human vs artificial) poses a challenge to the modeling of such complex environments. The overall aim of the work initiated with this paper is to build a rich model of agents’ interaction that is capable of providing guidance and possibly performance evaluation of real socio-technical systems.

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