Abstract-This paper describes the Infrastructure and Network Description Language (INDL). The aim of INDL is to provide technology independent descriptions of computing infrastructures. These descriptions include the physical resources and the network infrastructure that connects these resources. The description language also provides the necessary vocabulary to describe virtualization of resources and the services offered by these resources. Furthermore, the language can be easily extended to describe federation of different existing computing infrastructures, specific types of (optical) equipment and also behavioral aspects of resources, for example, their energy consumption.Before we introduce INDL we first discuss a number of modeling efforts that have lead to the development of INDL, namely the Network Description Language, the Network Markup Language and the CineGrid Description Language. We also show current applications of INDL in two EU-FP7 projects: NOVI and GEYSERS. We demonstrate the flexibility and extensibility of INDL to cater the specific needs of these two projects.

Analysis of student-tutor coaching dialogs suggest that good human tutors attend to and attempt to influence the motivational state of learners. Moreover, they are sensitive to the social face of the learner, and seek to mitigate the potential face threat of their comments. This paper describes a dialog generator for pedagogical agents that takes motivation and face threat factors into account. This enables the agent to interact with learners in a socially appropriate fashion, and foster intrinsic motivation on the part of the learner, which in turn may lead to more positive learner affective states.

This paper describes our approach to modeling computing infrastructures. Our main contribution is the Infrastructure and Network Description Language (INDL) ontology. The aim of INDL is to provide technology independent descriptions of computing infrastructures, including the physical resources as well as their network infrastructure. INDL also provides the necessary vocabulary to describe virtualization of resources and the services offered by these resources. We build our infrastructure model upon the Network Markup Language (NML). Although INDL is a stand-alone model, it can be easily connected with the NML model. In this paper we show how INDL and NML are used as a basis for models used in three different applications: the CineGrid infrastructure, the Logical Infrastructure Composition Layer in the GEYSERS EU-FP7 project and the NOVI federation platform. Furthermore, we show the use of INDL for monitoring energy aspects of computing infrastructures and its application for workflow planning on computing infrastructures.

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Abstract. In this chapter, we discuss the design of adaptive hierarchical organizations for multi-agent systems (MAS). Hierarchical organizations have a number of advantages such as their ability to handle complex problems and their scalability to large organizations. By introducing adaptivity in the structure of hierarchical MAS organizations, we enable agents to balance resources in their organization. We will first provide a number of generic principles for the design of hierarchical MAS organizations. We show how these principles are used to design three different hierarchical organizations for a search and rescue task in the RoboCupRescue simulation environment. The first two of these organizations are static, and the third is able to adapt its structure. An empirical study on the performance of these three organizations shows that the dynamic organization performs better than the two static organizations.

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Research in the area of Multi-Agent System (MAS) organization has shown that the ability for a MAS to adapt its organizational structure can be beneficial when coping with dynamics and uncertainty in the MASs environment. Different types of reorganization exist, such as changing relations and interaction patterns between agents, changing agent roles and changing the coordination style in the MAS. In this paper we propose a framework for agent Coordination and Reorganization (AgentCoRe) that incorporates each of these aspects of reorganization. We describe both declarative and procedural knowledge an agent uses to decompose and assign tasks, and to reorganize. The RoboCupRescue simulation environment is used to demonstrate how AgentCoRe is used to build a MAS that is capable of reorganizing itself by changing relations, interaction patterns and agent roles.