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Existing approaches for the verification of normative systems consider limited representations of norms, often neglecting collective imperatives, deadlines and contrary-to-duty obligations. In order to capture the requirements of real-world scenarios, these structures are important. In this paper we propose methods for the specification and formal verification of complex normative systems that include contrary-to-duty, collective and event-driven imperatives with deadlines. We propose an operational syntax and semantics for the specification of such systems. Using Maude and its linear temporal logic model checker, we show how important properties can be verified for such systems, and provide some experimental results for both bounded and unbounded verification.

In this paper we discuss how current ontology concepts can be beneficial for more flexible and semantic rich description of the authoring process and for the provision of authoring support of Intelligent Educational Systems (IES) with respect to the three main authoring modules: domain editing, course composition and resource management. We take a semantic perspective on the knowledge representation within such systems and explore the interoperability between the various ontological structures for domain, instructional and resource modeling and the modeling of the entire authoring process. We build upon our research on Authoring Task Ontology and exemplify it within OntoAIMS system. We present authoring scenarios and show their mapping with authoring task ontology. Further we discuss the OntoAIMS framework for management of electronic learning objects (resources) and their usage in the automatic generation of course templates for the authors. Finally, we describe our architecture, based on the ontological specification of the authoring process.

In this paper we present a rich decision model for intelligent agents involved in multi issue negotiations. The model, grounded on information theory, takes into account the aspects of trust and preference to devise mechanisms to manage dialogues. The model supports the design of agents that aim to take informed decisions taking into account that which they have actually observed.

This paper describes how cognitive modeling can be exploited in the design of software agents that support naval training sessions. The architecture, specifications, and embedding of the cognitive agent in a simulation environment are described. Subsequently, the agent's functioning was evaluated in complex, real life training situations for naval officers.