Research

Our group has been created in 2004 when Jürgen Dix was appointed full professor  for Theory and Computational Intelligence. From 2005 until 2010 two colleagues joined our group: Prof. Barbara Hammer (machine learning, datamining, statistical and relational learning) as well as apl. Prof. Matthias Reuter (softcomputing, pattern recognition, neural networks industrial applications)

 Our research and teaching activities center around

  • computational logic (deductive databases, answer set programming, nonmonotonic reasoning),
  • multi-agent systems (logics in agency, rational agents, programming agents), and
  • artificial intelligence (argumentation, verification, planning).

More details on our research projects and interests (and a comprehensive list of our publication), can be found in the research section.

    Members of our group actively participate in organizing conferences worldwide either as program comittee members, or as main organizers.

    For the convenience of the research community, we are running Event@CIG, a mailing list for distributing calls for papers and relevant announcements.

    We also organize the Multi-Agent Programming Contest, an international competition that strives to compare the performance measures of different multi-agent systems.

    We also extensively participate in teaching and other educational activities of the Department of Informatics by lecturing, seminar leading and integrating students into our project groups.

    Publications

    Publications
    Projects

    Projects
    Relations

    Relations
    Oberseminar

    Oberseminar

    My group is working on several aspects of reasoning about interaction of autonomous agents. You can have a look at our ***CIG complete publication list***. This broad area can be split into the following subareas: 

    1. Logics and logical formalisms
    2. Computational Logic
    3. The Multiagent Contest.

    1. Logics and logical formalisms

    • Logics: The last years have seen a plethora of attempts to combine knowledge and strategies in a single logical framework. How is uncertain information treated? Are there tractable fragments? How to combine knowledge and strategies for stochastic models? We plan to provide a toolbox that allows for verification of information- related properties in open IT environments of relatively small scale. [38, 39, 22, 14, 16, 28, 27].

      We have started several projects on:
      • Strategic Logics: (see [42, 41, 43, 44]).
      • Resource-bounded Agents: [17, 18, 16, 19]
      • Modular Interpreted Systems: [40, 45, 21].
      • Relations to Game Theory: game theory and extensions of strategic logics. See also [30, 13, 14, 20].
      • Petri nets: [7, 8, 9].

    2. Computational Logic

    Computational Logic: (answer set programming (ASP), belief revision, up- dates, argumentation, planning). We worked on the problem of representing knowledge in a dynamically changing world. and investigated belief revision in the con- text of logic programming updates and defined appropriate update semantics and classified them according to their formal properties. See [10, 2, 1, 35, 34, 36].

    We are working on argumentation techniques and how they can be incorporated into recommender systems and be used in multiagent systems ([26, 24, 31, 32, 11, 33]). A Dagstuhl Seminar will be organised in June 2013.

    We are developing logics to describe and reason about rational agents, in particu- lar to deal with coalitions. In our frameworks we incorporate plausibility reasoning, coalition formation and argumentation frameworks ([12, 13, 25]).

    The environment is an essential component of multiagent systems and is often used to coordinate the behaviour of individual agents. Recently many languages have been proposed to specify and implement multiagent environments in terms of social and normative concepts. We are working on a formal setting of multiagent environment which abstracts from concrete specification languages. This setting is based on norms and sanctions and we would like to show how concepts from mech- anism design can be used to formally analyse and verify whether specific normative behaviours can be enforced (or implemented) if agents follow their subjective preferences. [23, 15].

    3. The Multiagent Contest.

    Multiagent Programming Contest: We started the Agent Contest in 2005 based on discussions in the steering committee of CLIMA: It was felt that we need a competition event to evaluate and compare prototypes based on computational logic, where deliberation time is not considered critical (as in real-time applications). My group is organizing the contest ever since: www.multiagentcontest.org. It can be seen as an attempt to stimulate research in the area of multiagent system development and programming by (1) identifying key problems and (2) collecting suitable benchmarks, that can serve as milestones for testing multiagent programming languages, platforms and tools.

    The performance of a particular system is determined in a series of games where the systems compete against each other. While winning the competition is not the main point, we hope it will shed light on the applicability of certain frameworks to particular domains. See [6, 4, 3].

    While this is on the one hand an interesting testbed, in particular for Bachelor students, to experiment and learn about agent-programming languages, it also involves, on the other hand, theoretically important and nontrivial questions about the modelling of agents and their environment ([37, 5, 29]).

     

    References:

    [1] J. C. Acosta Guadarrama, J. Dix, and M. Osorio. Update sequences in generalised answer set programming based on structural properties. In Patrick Kellenberger, editor, Special Session of the 5th Interntational MICAI Conference, pages 32–41, Mexico City, Mexico, 2006. IEEE Computer Society.

    [2] J. C. Acosta Guadarrama, J. Dix, M. Osorio, and F. Zacarías. Updates in answer set programming based on structural properties. In S. McIlraith, P. Peppas, and M. Thielscher, editors, Proceedings of the 7th International Symposium on Logical Formalizations of Commonsense Reasoning, Technical Report Series, pages 213–219, Corfu, Greece, 2005. TU Dresden.

    [3] T. Behrens, M. Dastani, J. Dix, J. Hübner, M. Köster, P. Novák, and F. Schlesinger. The multi-agent programming contest. AI Magazine, 33(4):111–113, 2012.

    [4] T. Behrens, J. Dix, M. Köster, and J. Hübner, editors. Special Issue about Multi-Agent-Contest II, volume 61 of Annals of Mathematics and Artificial Intelligence. Springer, Netherlands, 2011.

    [5] Tristan Behrens, Rafael Bordini, Lars Braubach, Mehdi Dastani, Jürgen Dix, Koen Hindriks, Jomi Hübner, and Alexander Pokahr. An interface for agent-environment interaction. In Rem Collier, Jürgen Dix, and Peter Novák, editors, Proceedings of 8th international Workshop on Programming Multi-Agent Systems, ProMAS 2010, volume 6599 of LNCS, pages 170–185, Heidelberg, Germany, 2011. Springer Verlag.

    [6] Tristan Behrens, Mehdi Dastani, Jürgen Dix, Michael Köster, and Peter Novk. The multi-agent programming contest from 2005–2010: From collecting gold to herding cows. Annals of Mathematics and Artificial Intelligence, 59:277–311, 2010.

    [7] Tristan Behrens and Jürgen Dix. LTL model checking with logic based Petri nets. In M. Hanus and D. Seipel, editors, Proceedings of WLP ’07, volume 434 of Technical Report, pages 173– 182, Würzburg, Germany, October 2007. University of Würzburg.

    [8] Tristan Behrens and Jürgen Dix. Model checking with logic based Petri nets. In F. Sadri and K. Satoh, editors, Pre-Proceedings of CLIMA ’07, pages 6–21, Porto, Portugal, September 2007. Univesidade Do Porto.

    [9] Tristan Behrens and Jürgen Dix. Model checking multiagent systems with logic based Petri nets. Annals of Mathematics and Artificial Intelligence, 51(1–2):81–121, 2008.

    [10] R. Bordini, M. Dastani, J. Dix, and A. El Fallah Seghrouchni, editors. Programming Multi Agent Systems: Languages, Platforms and Applications, volume 15 of Multiagent Systems, Artificial Societies and Simulated Organizations. Springer, Berlin, 2005.

    [11] N. Bulling, J. Dix, and C. Chesn ̃evar. An argumentative approach for modelling coalitions using ATL. In I. Rahwan and P. Moraitis, editors, Proc. of the 5rd. Intl. Workshop on Argumentation and Multiagent Systems ArgMAS 2008 (Selected Contributions and Invited Papers), Lecture Notes, pages 190–211, Estoril, Portugal, May 2009. Springer.

    [12] N. Bulling and W. Jamroga. Agents, beliefs, and plausible behavior in a temporal setting. In Proceedings of AAMAS’07, pages 570–577, Honolulu, Hawaii, USA, 16–18 May 2007. ACM Press.

    [13] N. Bulling, W. Jamroga, and J. Dix. Reasoning about temporal properties of rational play. Annals of Mathematics and Artificial Intelligence, 53(1-4):51–114, 2008.

    [14] N. Bulling and W.Jamroga. Rational play and rational beliefs under uncertainty. In Proceedings of AAMAS’09, pages 257–264, Budapest, Hungary, May 2009. ACM Press.

    [15] Nils Bulling and Mehdi Dastani. Verification and implementation of normative behaviours in multi-agent systems. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI), pages 103–108, Barcelona, Spain, July 2011.

    [16] Nils Bulling, Jürgen Dix, and Wojciech Jamroga. Model checking logics of strategic ability: Complexity. In Mehdi Dastani, Koen V. Hindriks, and John-Jules Ch. Meyer, editors, Specification and Verification of Multi-Agent Systems, pages 125–158. Springer, 2010.

    [17] Nils Bulling and Berndt Farwer. Towards modelling and reasoning about resource-bounded systems. In Berndt Farwer, editor, Proceedings of Logics, Agents, and Mobility (LAM’09), pages 60–72, Los Angeles CA, USA, August 2009.

    [18] Nils Bulling and Berndt Farwer. Expressing properties of resource-bounded systems: The logics RBTL and RBTL∗. In J. Dix, M. Fisher, and P. Novak, editors, Post-Proceedings of CLIMA ’09, number 6214 in LNCS 6214, pages 22–45, Hamburg, Germany, September 2010.

    [19] Nils Bulling and Berndt Farwer. On the (Un-)Decidability of Model-Checking Resource-Bounded Agents. In Helder Coelho and Michael Wooldridge, editors, Proceedings of the 19th European Conference on Artificial Intelligence (ECAI 2010), pages 567–572, Porto, Portugal, August 16-20 2010.

    [20] Nils Bulling and Valentin Goranko. How to be both rich and happy: Combining quantitative and qualitative strategic reasoning about multi-player games. In Proceedings of the 1st International Workshop on Strategic Reasoning, Rome, Italy, March, 16-17 to appear in 2013.

    [21] Nils Bulling and Koen V. Hindriks. Taming the complexity of linear time BDI logics. In Proceedings of the 10th International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2011), pages 275–282, Taipei, Taiwan, May 2011. ACM Press.

    [22] Nils Bulling and Wojciech Jamroga. Model checking ATL+ is harder than it seemed. In Proceedings of the 7th European Workshop on Multi-Agent Systems EUMAS’09, pages 43–57, Ayia Napa, Cyprus, December 2009.

    [23] Nils Bulling and Wojciech Jamroga. Alternating epistemic mu-calculus. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI), pages 109–114, Barcelona, Spain, July 2011.

    [24] C. Chesn ̃evar, J. Dix, G. Simari, A. Maguitman, F. Stolzenburg, W. Jamroga, S. Gómez, and N. Bulling. Modelado de inferencia y preferencias en sistemas multiagentes utilizando argumentacion. In Zulema Rosanigo, editor, Proceedings of the IX Workshop of Researchers in Computer Science. Universidad Nacional de la Patagonia San Juan Bosco, pages 134–137, Trelew, Argentina, May 2007.

    [25] Jürgen Dix. Strategic abilities of agents. In Sven Hartmann and Gabriele Kern-Isberner, editors, Proceedings of the Fifth Conference on Foundations of Information and Knowledge Systems (FOIKS ’08), volume 4932 of Lecture Notes in Computer Science, page 7, Pisa, Italy, February 2008. Springer.

    [26] Jürgen Dix, C. Chesnevar, F. Stolzenburg, and G. Simari. Relating Defeasible and Normal Logic Programming through Transformation Properties. Theoretical Computer Science, 290(1):499–529, 2002.

    [27] Jürgen Dix and Michael Fisher. Where Logic and Agents meet. Annals of Mathematics and Artificial Intelligence, 61(1):15–28, 2011.

    [28] Jürgen Dix and Michael Fisher. Chapter 14: Verifying Multi-Agent Systems. In Gerhard Weiss, editor, Multiagent systems, pages 641–693. MIT-Press, 2013.

    [29] Jürgen Dix, Koen V. Hindriks, Brian Logan, and Wayne Wobcke. Engineering multi-agent systems (dagstuhl seminar 12342). Dagstuhl Reports, 2(8):74–98, 2012.

    [30] Jürgen Dix, Wojtek Jamroga, and Dov Samet. Reasoning about Interaction: From Game Theory to Logic and Back (Dagstuhl Seminar 11101). Dagstuhl Reports, 1(3):1–18, 2011.

    [31] Jürgen Dix, Simon Parsons, Henry Prakken, and Guillermo Simari. Dagstuhl manifesto. Informatik Spektrum, 32(1):70–81, 2009.

    [32] Jürgen Dix, Simon Parsons, Henry Prakken, and Guillermo Ricardo Simari. Research challenges for argumentation. Computer Science - R&D, 23(1):27–34, 2009.

    [33] Alejandro Garcia, Jürgen Dix, and Guillermo Simari. Argument-based logic programming. In Iyad Rahwani and Guillermo Simari, editors, Argumentation in Artificial Intelligence, pages 153–171. Springer, Berlin, 2009.

    [34] Juan C. Guadarrama. Implementing knowledge update sequences. In Alexander Gelbukh and Angel Kuri Morales, editors, MICAI 2007: Advances in Artificial Intelligence, volume 4827 of Lecture Notes in Computer Science, pages 1–8, Aguascalientes, Mexico, November 2007. Springer.

    [35] Juan C. Guadarrama. Maintaining knowledge bases at the object level. In Patrick Kellenberger, editor, Special Session of the 6th International MICAI Conference, Aguascalientes, Mexico, November 2007. IEEE Computer Society.

    [36] Juan Carlos Acosta Guadarrama. Update operation in asp revisited. Technical Report IfI-0812, Clausthal University of Technology, December 2008.

    [37] Koen Hindriks and Jürgen Dix. Goal: A multi-agent programming language applied to an exploration game. In Onn Shehory and Arnon Sturm, editors, Research Directions Agent-Oriented Software Engineering, pages 112–136. Springer, 2013.

    [38] W. Jamroga. Easy yet hard: Model checking strategies of agents. In Proceedings of CLIMA IX, pages 3–12, 2008.

    [39] W. Jamroga. A temporal logic for Markov chains. In L. Padgham, D. Parkes, J. Müller, and S. Parsons, editors, Proceedings of AAMAS’08, pages 697–704. IFAAMAS, 2008.

    [40] W. Jamroga and T.  ̊Agotnes. What agents can achieve under incomplete information. In Proceedings of AAMAS’06, pages 232–234, Hakodate, Japan, May 2006. ACM Press. Short paper.

    [41] W. Jamroga and J. Dix. Do agents make model checking explode (computationally)? In M. Pechoucek, P. Petta, and L. Z. Varga, editors, Multi-Agent Systems and Applications IV (CEEMAS 2005), volume 3690 of Lecture Notes in Computer Science, pages 398–407. Springer, 2005.

    [42] W. Jamroga and J. Dix. Turning game models turn-based for model checking properties of agents. In Katja Verbeeck, Karl Tuyls, Ann Nowé, Bernard Manderick, and Bart Kuijpers, editors, Proceedings of the 17th Belgian-Dutch Conference on Artificial Intelligence (BNAIC’05), pages 143–150, 2005.

    [43] W. Jamroga and J. Dix. Model checking abilities under incomplete information is indeed delta2-complete. In A. Omicini, B. Dunin-Keplicz, and J. Padget, editors, Proceedings of EUMAS’06, Lisbon, Portugal, December 2006.

    [44] Wojciech Jamroga and Jürgen Dix. Model checking abilities of agents: A closer look. Theory of Computing Systems, 42(3):366–410, 2008.

    [45] Michael Köster and Peter Lohmann. Abstraction for model checking modular interpreted systems over atl. In Louise Dennis, Olivier Boissier, and Rafael Bordini, editors, Programming Multi-Agent Systems, volume 7217 of Lecture Notes in Computer Science, pages 95–113. Springer Berlin / Heidelberg, 2012. 10.1007/978-3-642-31915-06.