Number of co-authors:13
Number of publications with 3 favourite co-authors:Jan Treur:6Egon L. van den Broek:2Alexei Sharpanskykh:2
Catholijn M. Jonker's 3 most productive colleagues in number of publications:Egon L. van den Br..:30Jan Treur:12Jeffrey M. Bradsha..:11
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Catholijn M. Jonker
Personal Homepage: mmi.tudelft.nl/~catholijn
Current place of employment: Delft University of Technology
Catholijn Jonker (1967) is full professor of Man-Machine Interaction at the Faculty of Electrical Engineering, Mathematics and Computer Science of the Delft University of Technology. She studied computer science, and did her PhD studies at Utrecht University. After a post-doc position in Bern, Switzerland, she became assistant (later associate) professor at the Department of Artificial Intelligence of the Vrije Universiteit Amsterdam. From september 2004 unitl september 2006 she was a full professor of Artificial Intelligence / Cognitive Science at the Nijmegen Institute of Cognition and Information of the Radboud University Nijmegen. She chaired De Jonge Akademie (Young Academy) of the KNAW (The Royal Netherlands Society of Arts and Sciences) in 2005 and 2006, and she is a member of the same organisation from 2005 through 2010.
Her recent publications address cognitive processes and concepts such as trust, negotiation, and the dynamics of individual agents and organisations. In Delft she works with an interdisciplinary team to engineer human experience through multi-modal interaction between natural and artificial actors in a social dynamic context. End 2007 her NWO-STW VICI project “Pocket Negotiator” has been awarded. In this project she develops intelligent decision support systems for negotiation.
Publications by Catholijn M. Jonker (bibliography)
Bradshaw, Jeffrey M., Dignum, Virginia, Jonker, Catholijn M. and Sierhuis, Maarten (2012): Human-agent-robot teamwork. In: Proceedings of the 7th International Conference on Human-Robot Interaction 2012. pp. 487-488.
Teamwork has become a widely accepted metaphor for describing the nature of multi-robot and multi-agent cooperation. By virtue of teamwork models, team members attempt to manage general responsibilities and commitments to each other in a coherent fashion that both enhances performance and facilitates recovery when unanticipated problems arise. Whereas early research on teamwork focused mainly on interaction within groups of autonomous agents or robots, there is a growing interest in leveraging human participation effectively. Unlike autonomous systems designed primarily to take humans out of the loop, many important applications require people, agents, and robots to work together in close and relatively continuous interaction. For software agents and robots to participate in teamwork alongside people in carrying out complex real-world tasks, they must have some of the capabilities that enable natural and effective teamwork among groups of people. Just as important, developers of such systems need tools and methodologies to assure that such systems will work together reliably and safely, even when they have been designed independently. The purpose of the HART workshop is to explore theories, methods, and tools in support of humans, agents and robots working together in teams. Position papers that combine findings from fields such as computer science, artificial intelligence, cognitive science, anthropology, social and organizational psychology, human-computer interaction to address the problem of HART are strongly encouraged. The workshop will formulate perspectives on the current state-of-the-art, identify key challenges and opportunities for future studies, and promote community-building among researchers and practitioners. The workshop will be structured around four two-hour sessions on themes relevant to HART. Each session will consist of presentations and questions on selected position papers, followed by a whole-group discussion of the current state-of-the-art and the key challenges and research opportunities relevant to the theme. During the final hour, the workshop organizers will facilitate a discussion to determine next steps. The workshop will be deemed a success when collaborative scientific projects for the coming year are defined, and publication venues are explored. For example, results from the most recent HART workshop (Lorentz Center, Leiden, The Netherlands, December 2010) will be reflected in a special issue of IEEE Intelligent Systems on HART that is slated to appear in January/February 2012.
© All rights reserved Bradshaw et al. and/or their publisher
Hoogendoorn, Mark, Gini, Maria L. and Jonker, Catholijn M. (2007): Decentralized task allocation using magnet: an empirical evaluation in the logistics domain. In: Gini, Maria L., Kauffman, Robert J., Sarppo, Donna, Dellarocas, Chrysanthos and Dignum, Frank (eds.) Proceedings of the 9th International Conference on Electronic Commerce - ICEC 2007 August 19-22, 2007, Minneapolis, MN, USA. pp. 319-328.
Bosse, Tibor, Jonker, Catholijn M. and Treur, Jan (2006): Formalization and Analysis of Reasoning by Assumption. In Cognitive Science, 30 (1) pp. 147-180.
Broek, Egon L. van den, Jonker, Catholijn M., Sharpanskykh, Alexei, Treur, Jan and Yolum, Pinar (2006): Formal Modeling and Analysis of Organizations. In: Boissier, Olivier, Padget, Julian A., Dignum, Virginia, Lindemann, Gabriela, Matson, Eric T., Ossowski, Sascha, Sichman, Jaime Simão and Vázquez-Salceda, Javier (eds.) AAMAS 2005 International Workshops on Agents, Norms and Institutions for Regulated Multi-Agent Systems, ANIREM 2005, and Organizations in Multi-Agent Systems, OOOP 2005, Utrecht, 2006. pp. 18-34.
Broek, Egon L. van den, Jonker, Catholijn M., Sharpanskykh, Alexei, Treur, Jan and Yolum, Pinar (2005): Formal Modeling and Analysis of Organizations. In: Verbeeck, Katja, Tuyls, Karl, Nowé, Ann, Manderick, Bernard and Kuijpers, Bart (eds.) BNAIC 2005 - Proceedings of the Seventeenth Belgium-Netherlands Conference on Artificial Intelligence October 17-18, 2005, Brussels, Belgium. pp. 391-392.
Jonker, Catholijn M. and Treur, Jan (2002): Modelling multiple mind-matter interaction. In International Journal of Human-Computer Studies, 57 (3) pp. 165-214.
Relations between mental and physical aspects of an agent can be of various
types. Sensing and acting are among the more commonly modelled types. In agent
modelling approaches often this is the only interaction between the physical
and mental; other possible types of interactions are abstracted away. If it is
also taken into account that the agent's mind has a materialization in the form
of a brain, the relations between mind and matter may become more complex. An
explanation of a dynamic pattern may involve mental aspects, physical aspects,
and interactions between mental and physical aspects. An explanatory
perspective sometimes advocated for such more complex phenomena is explanatory
pluralism. According to this perspective an explanation can consist of parts of
a different signature, for example, a partial physical explanation and a
partial mentalistic explanation. Each of these partial explanations is
insufficient to explain the whole phenomenon, but together they do explain the
whole, if some interaction is assumed. How for such explanations the different
types of interaction between mind and matter of an agent and the material world
can be modelled in a conceptually and semantically sound manner, and how the
overall explanation is composed from the parts, using these interactions, is
the main topic of this paper. The generic model presented can be used to model,
explain and simulate a variety of phenomena in which multiple mind-matter
interactions occur, including, for example, sensing and acting, (planned) birth
and death, bacterial behaviour, getting brain damage, psychosomatic diseases
and applications of direct brain-computer interfaces.
© All rights reserved Jonker and Treur and/or Academic Press
Jonker, Catholijn M., Treur, Jan and Wijngaards, Wouter C. A. (2001): An Agent-Based Architecture for Multimodal Interaction. In International Journal of Human-Computer Studies, 54 (3) pp. 351-405.
In this paper, an executable generic process model is proposed for combined verbal and non-verbal communication processes and their interaction. The agent-based architecture can be used to create multimodal interaction. The generic process model has been designed, implemented and used to simulate different types of interaction between verbal and non-verbal communication processes: a non-verbal communication process can add and modify content to a verbal communication process, but can also provide a protocol for the (control of the) verbal communication process. With respect to the communication protocol both stimulus-response behaviour and deliberative behaviour have been modelled and simulated. The semantics of the model has been formalized by three-levelled partial temporal models, covering both the material and mental proceses and their relations.
© All rights reserved Jonker et al. and/or Academic Press
Brazier, Frances M. T., Jonker, Catholijn M., Treur, Jan and Wijngaards, Niek J. E. (2000): On the Use of Shared Task Models in Knowledge Acquisition, Strategic User Interaction and Clarification Agents. In International Journal of Human-Computer Studies, 52 (1) pp. 77-110.
In this paper, three different roles of a shared task model as an intermediate representation of a task are presented and illustrated by applications developed in cooperation with industry. First the role of a shared task model in knowledge acquisition is discussed. In one of the two applications, decision support in the domain of soil sanitation, one of the existing generic task models for diagnostic reasoning provided a means to structure knowledge acquisition. In the second application, diagnosis of chemical processes, the acquisition process resulted in a shared task model for diagnostic reasoning on Nylon-6 production. Secondly, the role of a shared task model in designing user interaction is addressed. Three levels of interaction are considered of importance: interaction at the object level, at the level of strategic preferences, and at the level of task modification. In an application in the domain of environmental decision making, this led to the design of a user interface based on the acquired shared task model, within which all three levels of interaction were available to users. Finally, the role of shared task models within a multi-agent system including a clarification agent is addressed. Two software agents were designed that each share a task model with the user: one for a diagnosis task, and one for a clarification task. The shared model of the clarification task reflects the shared task model of diagnosis; clarification includes clarification of the overall diagnostic reasoning process. The multi-agent architecture presented has been developed to support a user both at the level of the diagnostic task he or she is performing and at the level of clarification. The architecture has been applied to the diagnosis of chemical processes.
© All rights reserved Brazier et al. and/or Academic Press
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