Abstract: This paper appeared at the ISCRAM 2010  and presents an intelligent system facilitating better in-
formed decision making under severe uncertainty, as often found in emergency management. The
construction of decision-relevant scenarios, being plausible descriptions of a situation and its future
development, is used as a rationale for collecting, organizing, filtering and processing information for
decision making. The development of scenarios is geared to assessing decision alternatives, thus avoiding
time-consuming analysis and processing of irrelevant information.
The scenarios are constructed in a distributed setting allowing for a flexible adaptation of reasoning (prin-
ciples and processes) to the problem at hand and the information available. Each decision can be founded
on a coherent set of scenarios, which was constructed using the best expertise available within a limited
timeframe. Our theoretical framework is demonstrated in a distributed decisionsupport system by
orchestrating both automated systems and human experts into workflows tailored to each specific problem.
Abstract: Emergency situations occur unpredictably and cause individuals and organizations to shift their focus and attention immediately to dealing with the situation. When disasters become large in scale all the limitations resulting from a lack of integration and collaboration among all the involved organizations begin to expose themselves and further compound the negative consequences of the event. Often in large scale disasters the people who must work together have no history of doing so, they have not developed a trust or understanding of one anotherís abilities, and the totality of resources they each bring to bear were never before exercised. As a result, the challenges for individual or group decisionsupportsystems (DSS) in emergency situations are diverse and immense. In this chapter, we present recent advances in this area and highlight important remaining challenges.
Abstract: The increasing complexity of our world demands new perspectives on the role of technology in human decision making. We need new technology to cope with the increasingly complex and information-rich nature of our modern society. This is particularly true for critical environments such as crisis management and traffic management, where humans need to engage in close collaborations with artificial systems to observe and understand the situation and respond in a sensible way. The book Interactive Collaborative Information Systems addresses techniques that support humans in situations in which complex information handling is required and that facilitate distributed decision-making. The theme integrates research from information technology, artificial intelligence and human sciences to obtain a multidisciplinary foundation from which innovative actor-agent systems for critical environments can emerge. It emphasizes the importance of building actor-agent communities: close collaborations between human and artificial actors that highlight their complementary capabilities in situations where task distribution is flexible and adaptive. This book focuses on the employment of innovative agent technology, advanced machine learning techniques, and cognition-based interface technology for the use in collaborative decisionsupportsystems.
Abstract: Humans primarily assess situations and plan for actions by (implicit) scenario-based analysis. Decision making in crisis management situations in The Netherlands unfortunately does not explicitly feature scenario-based analysis; not within teams nor between teams. In this article we formulate conditions for successful application of scenario-based analysis, based on our experiences in crisis management and crisis management exercises. The conditions are formulated and briefly assessed in a number of cases. An important implication for information systemssupport is identified and future research is announced.
Abstract: This paper introduces the MultiAgent Decision Process software toolbox, an open source C++ library for decision-theoretic planning under uncertainty in multiagent systems. It provides support for several multiagent models, such as POSGs, Dec-POMDPs and MMDPs. The toolbox aims to reduce development time for planning algorithms and to provide a benchmarking platform by providing a number of commonly used problem descriptions. It features a parser for a text-based ﬁle format for discrete Dec-POMDPs, shared functionality for planning algorithms, as well as the implementation of several Dec-POMDP planners. We describe design goals and architecture of the toolbox, and provide an overview of its functionality, illustrated by some usage examples. Finally we report on current and future work.
Abstract: Collaboration environments impose high demands on humans and
artificial systems. Especially during critical tasks team members, including
humans, artificial systems and other (sub-) teams, require support to guarantee
their continued effectiveness. Effectiveness of individuals and teams is an
important ingredient for organizational effectiveness, managerial decision
quality, as well as for maintaining organizational awareness. In this position
paper we introduce our conceptual view on realizing sustained team
effectiveness, in which both the measurement of effectiveness and team
management play an important role. A unified, interdisciplinary approach
facilitates measuring effectiveness in more complex organizations.
Abstract: Collaboration environments impose high demands on humans and artificial systems. Especially during critical tasks team members, including humans, artificial systems and other (sub-) teams, require support to guarantee their continued effectiveness. Effectiveness of individuals and teams is an important ingredient for organizational effectiveness, managerial decision quality, as well as for maintaining organizational awareness. In this position paper we introduce our conceptual view on realizing sustained team effectiveness, in which both the measurement of effectiveness and team management play an important role. A unified, interdisciplinary approach facilitates measuring effectiveness in more complex organizations.