Abstract: This chapter gives an overview of the state of the art in decision-theoretic models to describe cooperation between multiple agents in a dynamic environment.
Making (near-) optimal decisions in such settings gets harder when the number of agents grows or the uncertainty about the environment increases. It is essential to have compact models, because otherwise just representing the decision problem
becomes intractable. Several such model descriptions and approximate solution methods, studied in the Interactive Collaborative Information Systems project, are presented and illustrated in the context of crisismanagement.
Abstract: This deliverable is a state of the art on automated negotiation techniques for multi-agent systems.
Negotiation is a subject of research in a variety of domains, such as social choice, economics,
rhetoric, game theory, multi-criteria decision making, knowledge management, and so on, from
many years but the automated negotiation in a multi-agent environment has only less than ten
years old. Therefore, we present main techniques used in multi-agent systems enabling
automated negotiation such as voting, bargaining, auctions and contracting.
Negotiation is used to solve more efficiently logistics and crisismanagement problems, among
others, when at least two parties are involved in the decision process. Most of the current
negotiation approaches only deal with problems concerning mono-dimensional negotiation, i.e.
which only concern a single negotiation dimension, such as allocating a single task to a co-
workers. But recently, some studies have been conducted on the topic of combined negotiations,
in which the negotiation process concerns multiple interrelated objectives, a more realistic
modeling of what occurs in real world applications. Therefore, we suggest to study the problem of
multi-criteria and combined negotiation in multi-agents systems by first realizing a state of the art
on negotiation techniques for multi-agent systems.
Abstract: Information Systems for Crisis Response and Management (ISCRAM) are often statically built around the dominant
design view of a known/knowable context. In this paper we will argue why this does not constitute a good design
strategy by examining the need of avoiding dealing with the wrong problem (Type III errors) and by relating our
findings to a contextual framework like Cynefin. We rely on the insight form High Reliability Theory (HRT) to
avoid simplification to find the balance between a recommendation to design for complexity and a prevention of
Type III errors.
Abstract: When we talk about improving Information Systems for Crisis Response and Management, we must consider at least two sorts of problems to solve: the processing of human provided information (perception and knowledge) in combination with other sensor information and the human processing of sensor based information (for situation awareness and decision making). As an illustration, two examples of research work that is done at the D-CIS lab in Delft is presented here. The first example is about Distributed Perception Networks in disaster management and the second example is about cognitive performance factors in decision making (in crisis situations).
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 crisismanagement 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 decision support systems.
Abstract: This paper reintroduces concepts from sensemaking in Media Synchronicity Theory (MST). It focuses on how media should support synchronicity to fit communication needs when making sense of a humanitarian crisis situation. Findings from interviews with senior management of humanitarian aid organizations in the Democratic Republic of Congo show that, contrary to what is suggested by MST, low synchronicity media are not sufficient to support conveyance processes. Instead, information and communication systems should support these actors in connecting, building, and maintaining their networks of contacts. Also, information and communications systems need to be designed to support the observed sensemaking communication activities of noticing, updating, inquiring, triangulating, verifying, reflecting, enacting, and interpreting.
Abstract: Advances in network technologies enable distributed systems, operating in complex physical environments, to co-ordinate their activities over larger areas within shorter time intervals. Some envisioned application domains for such systems are defence, crisismanagement, traffic management and public safety. In these systems humans and machines will, in close interaction, be adaptive to a changing environment. Various architecture models are proposed for such Networked Adaptive Interactive Hybrid Systems (NAIHS) from different research areas like (networked) sensor fusion, command and control, artificial intelligence, robotics and human machine interaction. In this paper an architecture model is proposed that seeks to combine their merits. The NAIHS model focuses on the ‘hybrid mind’ that is layered in several dimensions
defining specific functional components and their
interactions. Subsequently, the interaction between the human and artificial part of the system is discussed.
Abstract: Negotiation is used to solve more efficiently logistics and crisismanagement problems, among others, when at least two parties are involved in the decision process. Most of the current negotiation approaches only deal with problems concerning mono-dimensional negotiation, i.e. which only concern a single negotiation dimension, such as allocating a single task to a co-workers. But recently, some studies have been conducted on the topic of combined negotiations, in which the negotiation process concerns multiple interrelated objectives, a more realistic modeling of what occurs in real world applications. Therefore, we suggest to study the problem of multi-criteria and combined negotiation in multi-agents systems by designing a new protocol to solve some of existing negotiation problems.
This deliverable follows a previous one, a report titled “Cooperation-based Multilateral Multi-issue Negotiation for CrisisManagement” (Hemaissia et al., 2006). The negotiation protocol proposed here, is suited for multiple agents with complex preferences and taking into account, at the same time, multiple interdependent issues and recommendations made by the agents to improve a proposal.
Abstract: Humans primarily assess situations and plan for actions by (implicit) scenario-based analysis. Decision making in crisismanagement 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 crisismanagement and crisismanagement exercises. The conditions are formulated and briefly assessed in a number of cases. An important implication for information systems support is identified and future research is announced.
Abstract: International humanitarian aid and development organizations active in the Democratic Republic of Congo (DRC) are faced with an ongoing crisis situation. Using any formal or informal information source available, they are constantly acquiring and processing information that may indicate the possible surge of an acute crisis. Information systems (IS) that enable effective and efficient information processing and decision making within and among the organizations are therefore a critically important asset to these organizations. We present a concise set of design premises that have been developed for dynamic emergency response management information systems, and we introduce the theory of Sensemaking as a lens to observe and analyze the information processing and decision making behavior of organizations. Based on interviews conducted among senior management of international aid and development organizations operating in the DRC, our findings illustrate the constant Sensemaking behavior of these organizations and provide a motivation for the proposed IS design premises.
Abstract: This paper attempts to reveal the “black box” of information processing activities by relying on Sensemaking as a
methodology and as the object of research. In particular, this research aims at studying intuitive information
processing activities in ongoing crisis situations, one of the most extreme contexts in which discontinuity is the rule
and continuity the exception. The authors argue that this Sensemaking approach offers valuable insights for the
design of information systems for crisis response and management (ISCRAM). This paper describes an interpretive
case study methodology as it was applied to discover Sensemaking episodes in the daily work of humanitarian relief
actors in the ongoing crisis of the Democratic Republic of Congo.
Abstract: Conducting empirical research involves a balancing act between scientific rigor and real-life pragmatics. The Delft Co-operation on Intelligent Systems (D-CIS) laboratory researches systems-of-systems consisting of the human and artificial systems involved in collaborative decision-making under chaotic circumstances. An important objective is the usefulness of our results in our major application domain: crisismanagement. The D-CIS lab was involved in setting up a crisismanagement exercise experiment and the according measurements regarding an improvement in internal communication at Gemeente (Municipality) Borsele. In this paper, the empirical research regarding this experiment, the methodology and its results are briefly outlined. The main lessons learned concern the interrelationship between the scenario, experiment and measurements, the problem of acquiring usable data and the challenges of conducting grounded research.
Abstract: Conducting empirical research involves a balancing act between scientific rigor and real-life pragmatics. DECIS Lab researches systems-of-systems, consisting of humans and artificial systems involved in collaborative decision making under chaotic circumstances. An important objective is the usefulness of our results to our major application domain: crisismanagement. DECIS Lab was involved to set up a crisismanagement exercise experiment and according measurements regarding an improvement in internal communication at Gemeente (Municipality) Borsele. In this paper the empirical research regarding this experiment, the methodology and its results are briefly outlined. Our main lessons learned concern the interrelationship between scenario, experiment and measurements; the problem of acquiring usable data; and the challenges of conducting grounded research.
Abstract: In the past a crisis event was notified by local witnesses that use to make phone calls to the special services. They reported by speech according to their observation on the crisis site. The recent improvements in the area of human computer interfaces make possible the development of context-aware systems for crisismanagement that support people in escaping a crisis even before external help is available at site. Apart from collecting the people's reports on the crisis, these systems are assumed to automatically extract useful clues during typical human computer interaction sessions. The novelty of the current research resides in the attempt to involve computer vision techniques for performing an automatic evaluation of facial expressions during human-computer interaction sessions with a crisismanagement system. The current paper details an approach for an automatic facial expression recognition module that may be included in crisis-oriented applications. The algorithm uses Active Appearance Model for facial shape extraction and SVM classifier for Action Units detection and facial expression recognition.