Interactive Collaborative Information Systems

1. Front Matter

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2. Reinforcement Learning

   1. Front Matter

      Pages 1-1

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   2. Approximate Dynamic Programming and Reinforcement Learning

      • Lucian Buşoniu, Bart De Schutter, Robert Babuška

      Pages 3-44

   3. Learning with Whom to Communicate Using Relational Reinforcement Learning

      • Marc Ponsen, Tom Croonenborghs, Karl Tuyls, Jan Ramon, Kurt Driessens, Jaap van den Herik et al.

      Pages 45-63

   4. Switching between Representations in Reinforcement Learning

      • Harm van Seijen, Shimon Whiteson, Leon Kester

      Pages 65-84

3. Collaborative Decision Making

   1. Front Matter

      Pages 85-85

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   2. A Decision-Theoretic Approach to Collaboration: Principal Description Methods and Efficient Heuristic Approximations

      • Frans A. Oliehoek, Arnoud Visser

      Pages 87-124

   3. Efficient Methods for Near-Optimal Sequential Decision Making under Uncertainty

      • Christos Dimitrakakis

      Pages 125-153

   4. Ant Colony Learning Algorithm for Optimal Control

      • Jelmer Marinus van Ast, Robert Babuška, Bart De Schutter

      Pages 155-182

   5. Map-Based Support for Effective Collaboration in Micro-mobile Virtual Teams

      • Guido te Brake, Rick van der Kleij

      Pages 183-203

4. Computer-Human Interaction Modeling

   1. Front Matter

      Pages 205-205

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   2. Affective Dialogue Management Using Factored POMDPs

      • Trung H. Bui, Job Zwiers, Mannes Poel, Anton Nijholt

      Pages 207-236

   3. Context-Aware Multimodal Human–Computer Interaction

      • Siska Fitrianie, Zhenke Yang, Dragoş Datcu, Alin G. Chiţu, Léon J. M. Rothkrantz

      Pages 237-272

   4. Design Issues for Pen-Centric Interactive Maps

      • Louis Vuurpijl, Don Willems, Ralph Niels, Marcel van Gerven

      Pages 273-297

   5. Interacting with Adaptive Systems

      • Vanessa Evers, Henriette Cramer, Maarten van Someren, Bob Wielinga

      Pages 299-325

   6. Example-Based Human Pose Recovery under Predicted Partial Occlusions

      • Ronald Poppe

      Pages 327-354

5. Architectures for Distributed Agent-Actor Communities

   1. Front Matter

      Pages 355-355

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   2. Agility and Adaptive Autonomy in Networked Organizations

      • Martijn Neef, Bob van der Vecht

      Pages 357-373

   3. Adaptive Hierarchical Multi-agent Organizations

      • Mattijs Ghijsen, Wouter N. H. Jansweijer, Bob J. Wielinga

      Pages 375-400

   4. Method for Designing Networking Adaptive Interactive Hybrid Systems

      • Leon Kester

      Pages 401-421

The increasing complexity of our world demands new perspectives on the role of technology in decision making. Human decision making has its li- tations in terms of information-processing capacity. 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 tra?c management, where humans need to engage in close collaborations with arti?cial systems to observe and understand the situation and respond in a sensible way. We believe that close collaborations between humans and arti?cial systems will become essential and that the importance of research into Interactive Collaborative Information Systems (ICIS) is self-evident. Developments in information and communication technology have ra- cally changed our working environments. The vast amount of information available nowadays and the wirelessly networked nature of our modern so- ety open up new opportunities to handle di?cult decision-making situations such as computer-supported situation assessment and distributed decision making. To make good use of these new possibilities, we need to update our traditional views on the role and capabilities of information systems. The aim of the Interactive Collaborative Information Systems project is to develop techniques that support humans in complex information en- ronments and that facilitate distributed decision-making capabilities. ICIS emphasizes the importance of building actor-agent communities: close c- laborations between human and arti?cial actors that highlight their comp- mentary capabilities, and in which task distribution is ?exible and adaptive.

• Bayesian network
• agent technology
• algorithms
• artificial intelligence
• cognition
• complexity
• decision support system
• expert system
• information system
• intelligence
• learning
• machine learning
• modeling
• reinforcement learning
• uncertainty

• Delft Center for Systems and Control, Delft University of Technology, Delft, The Netherlands

  Robert Babuška

• Faculty of Science, Informatics Institute, Amsterdam, The Netherlands

  Frans C. A. Groen

Policies and ethics