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Gary Berg-Cross. (2008). Improving situational ontologies to support adaptive crisis management knowledge architecture. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 537–545). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: There is considerable interest in advance technologies to support crisis and disaster management as they face the challenges of designing, building, and maintaining large-scale distributed systems able to adapt to the dynamics and complexity of crises. Candidate technologies include Service Oriented Architecture (SOA), related Semantic Web technology, agent-based architecture and cognitive architectures. Each embodies some principles of the Adaptive Architecture-including modularity, openness, standards-based development, runtime support and importantly explicitness. However, truly adaptive architectures for crisis management will require some deepening the knowledge architecture's content and not just its representation. Light and more robust ontological models of situations are discussed to show how better formalization of conceptual patterns like “participation” can be developed to support cognitive architectures. The feasibility of an ontological design pattern approach is described as an avenue for future research and development describing specific types of situations.
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Rosemarijn Looije, Mark A. Neerincx, & Geert-Jan M. Kruijff. (2007). Affective collaborative robots for safety & crisis management in the field. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 497–506). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The lack of human-robot collaboration currently presents a bottleneck to widespread use of robots in urban search & rescue (USAR) missions. The paper argues that an important aspect of realizing human-robot collaboration is collaborative control, and the recognition and expression of affect. Affective collaborative robots can enhance joint human-robot performance by adapting the robot's (social) role and interaction to the user's affective state and the context. Current USAR robots lack these capabilities. This paper presents theory, application domains, and requirements for affective collaborative robots based on the current state of the art. With methods from cognitive architectures, affective computing, and human-robot interaction, three core functions of affective collaborative robots can be realized: sliding autonomy, affective communication, and adaptive attitude. These robot functions can substantially enhance the efficiency and effectiveness of rescue workers and meanwhile reduce their cognitive workload. Furthermore, robots with such functions can approach civilians in the field appropriately.
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