Publications by Consortium Members

Arslan, B., N. A. Taatgen and R. Verbrugge (2017). “Five-Year-Olds’ Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection.” Front Psychol 8: 275.

Aydogan, R., I. Marsa-Maestre, M. Klein and C. M. Jonker (2018). “A Machine Learning Approach for Mechanism Selection in Complex Negotiations.” J. of Systems Science and Systems Engineering 27: 134-155.

Baarslag, T., M. Kaisers, E. H. Gerding, C. M. Jonker and J. Gratch (2017). “When will negotiation agents be able to represent us? The challenges and opportunities for autonomous negotiators.”, IJCAI.

Balliet, D. (2010). “Communication and cooperation in social dilemmas: a meta-analytic review.” J. of conflict resolution 54(1): 39-57.

Balliet, D., J. M. Tybur and P. A. M. Van Lange (2017). “Functional Interdependence Theory: An Evolutionary Account of Social Situations.” Pers Soc Psychol Rev 21(4): 361-388.

Balliet, D., J. Wu and D. Dreu (2014). “Ingroup favoritism in cooperation: a meta-analysis.” Psychological Bulletin 140(6): 1556.

Balliet, D. P., L. Mulder and P. A. M. van Lange (2011). “Reward, punishment, and cooperation: A meta-analysis.” Psychological Bulletin 137: 594-615.

Balliet, D. P. and P. A. M. van Lange (2013). “Trust, conflict and cooperation: A meta-analysis.” Psychological Bulletin 139(5): 1090-1112.

Barbaros, V., A. Abdolmaleki, H. van Hoof and D. Meger (2018). “Eager and memory-based non-parametric stochastic search methods for learning control.” Int. Conf. Robotics and Automation.

Bex, F. J., H. Prakken, T. Van Engers and B. Verheij (2017). “Introduction to the special issue on Artificial Intelligence for Justice.” Artificial Intelligence and Law 25(1): 1-3.

Bosse, T. and C. M. Jonker (2005). “Human vs. computer behavior in multi-issue negotiation.” Rational, Robust, and Secure Negotiation Mechanisms in Multi-Agent Systems: 11-24.

Bosse, T., C. M. Jonker, L. van der Meij and J. Treur (2008). “Automated Formal Analysis of Human Multi-Issue Negotiation Processes.” Multiagent and Grid Systems 4(2): 213-233.

Boumans, R., F. Fokke van Meulen, K. Hindriks, M. Neerincx and M. O. Rikkert (2018). Do You Have Pain?: A Robot who Cares. ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI ’18).

Bradshaw, J. M., V. Dignum, C. Jonker and M. Sierhuis (2012). “Human-agent-robot teamwork.” IEEE Intelligent Systems 27: 8-13.

Burger, F., J. Broekens and M. A. Neerincx (2016). A Disclosure Intimacy Rating Scale for Child-Agent Interaction Book, Springer.

Burger, F., J. Broekens and M. A. Neerincx (2016). Fostering relatedness between children and virtual agents through reciprocal self-disclosure. In Benelux Conf. on Artificial Intelligence, Springer, Cham.

Dastani, M., D. Grossi, J. J. C. Meyer and N. Tinnemeier (2009). Normative multi-agent programs and their logics. In Knowledge Representation for Agents and Multi-Agent Systems. Knowledge Representation for Agents and Multi-Agent Systems, Springer: 16-31.

de Greeff, J., T. Mioch, W. van Vught, K. Hindriks, M. Neerincx and I. Kruijff-Korbayová (2018). Persistent Robot-Assisted Disaster Response. ACM/IEEE Int. Conf. on Human-Robot Interaction.

de Weerd, H., D. Diepgrond and R. Verbrugge (2018). “Estimating the use of higher-order theory of mind using computational agents.” The BE J. of Theoretical Economics 18(2): 12.

de Weerd, H., R. Verbrugge and B. Verheij (2013). “How much does it help to know what she knows you know? An agent-based simulation study.” Artificial Intelligence 199: 67-92.

de Weerd, H., R. Verbrugge and B. Verheij (2017). “Negotiating with other minds: The role of recursive theory of mind in negotiation with incomplete information.” AAMAS 31(2): 250–287.

Dignum, F., B. Dunin-Keplicz and R. Verbrugge (2001). Agent Theory for Team Formation by Dialogue. Intelligent Agents VII, Agent Theories Architectures and Languages, Springer: 150-166.

Dudzik, B., H. Hung, M. A. Neerincx and J. Broekens (2018). Artificial Empathic Memory: Enabling Media Technologies to Better Understand Subjective User Experience. In Proc. of ACM MultiMedia.

Dunin-Kęplicz, B., A. Strachocka and R. Verbrugge (2011). Deliberation dialogues during multi-agent planning. Int. Symp. on Methodologies for Intelligent Systems. Berlin, Heidelberg, Springer: 170-181.

Dunin-Keplicz, B. and R. Verbrugge (2003). “Evolution of collective commitment during teamwork.” Fundamental Informatics 56(4): 329-371.

Dunin-Keplicz, B. and R. Verbrugge (2010). Teamwork in Multi-Agent Systems: A Formal Approach. Chichester, Wiley.

Dunin-Kȩplicz, B. and R. Verbrugge (2006). Awareness as a vital ingredient of teamwork. AAMAS.

Eggensperger, K., M. T. Lindauer, H. H. Hoos, F. Hutter and K. Leyton-Brown (2018). “Efficient Benchmarking of Algorithm Configuration Procedures via Model-Based Surrogates.” Machine Learning 107: 15–41.

Eiben, A. E. and J. Smith (2015). “From evolutionary computation to the evolution of things.” Nature 521(476).

Fokkens, A. S., P. Vossen, M. Rospocher, R. Hoekstra and W. van Hage (2017). Grasp: grounded representation and source perspective. Proc. of Knowledge Resources for the Socio-Economic Sciences and Humanities.

Garmash, E. and C. Monz (2016). Ensemble Learning for Multi-Source Neural Machine Translation. Proc. of the 26th Int. Conf. on Computational Linguistics.

Gerpott, F. H., D. Balliet, S. Columbus, C. Molho and R. E. de Vries (2018). “How do people think about interdependence? A multidimensional model of subjective outcome interdependence.” J Pers Soc Psychol 115(4): 716-742.

Ghader, H. and C. Monz (2017). What does Attention in Neural Machine Translation Pay Attention to? Proc. of the Int. Joint Conf. on Natural Language Processing.

Grossi, D. and P. Turrini (2012). “Dependence in Games and Dependence Games. J. of Autonomous Agents and Multi-Agent Systems.” Springer 25(2): 284–312.

Gunes, H. and H. Hung (2016). “Is automatic facial expression recognition of emotions coming to a dead end? The rise of the new kids on the block.” Image and Vision Computing 55: 6-8.

Guttmann, C., F. Dignum and M. Georgeff (2011). Collaborative Agents – Research and Development, Springer.

Haasdijk, E., A. E. Eiben and A. F. T. Winfield (2013). Individual, Social and Evolutionary Adaptation in Collective Systems. Handbook of Collective Robotics: Fundamentals and Challenges. S. Kernbach, Pan Stanford Publishers: 413-471.

Harbers, M., R. Aydogan, C. M. Jonker and M. A. Neerincx (2014). Sharing Information in Teams: Giving Up Privacy or Compromising on Team Performance? Proc. of the 13th AAMAS, Paris.

Harbers, M., J. de Greeff, I. Kruijff-Korbayová, M. A. Neerincx and K. V. Hindriks (2017). Exploring the ethical landscape of robot-assisted Search and Rescue. World with Robots, Springer: 93-107.

Harbers, M. and M. A. Neerincx (2017). “Value sensitive design of a virtual assistant for workload harmonization in teams.” Cognition, Technology and Work 19(2-3): 329-343.

Heinerman, J., E. Haasdijk and A. E. Eiben (2017). “Unsupervised identification and recognition of situations for high-dimensional sensori-motor streams.” Neurocomputing 262: 90-107.

E.M. Helsper, L.C. van der Gaag (2007). Ontologies for probabilistic networks: a case study in the oesophageal-cancer domain. The Knowledge Engineering Review 22: 67 — 86.

Henkemans, O. A. B., B. P. Bierman, J. Janssen, R. Looije, M. A. Neerincx, M. M. van Dooren and S. D. Huisman (2017). “Design and evaluation of a personal robot playing a self-management education game with children with diabetes type 1.” Int. J. of Human-Computer Studies 106: 63-76.

Hindriks, K., C. Jonker and D. Tykhonov (2008). “Towards an Open Negotiation Architecture for Heterogeneous Agents.” Cooperative Information Agents XII 5180.

Hindriks, K. V. and C. M. Jonker (2009). Creating human-machine synergy in negotiation support systems: towards the pocket negotiator. Proc. of the 1st Int. Working Conf. on Human Factors and Computational Models in Negotiation. New York: 47-54.

Hofstede, G. J., C. M. Jonker and T. Verwaart (2012). “Cultural differentiation of negotiating agents.” Group Decision and Negotiation 21(1): 79-98.

Horsch, C. H. G., N. J. J. M. Smets, M. A. Neerincx and R. H. Cuijpers (2013). Comparing performance and situation awareness in USAR unit tasks in a virtual and real environment. 10th Int. Conf. on Information Systems for Crisis Response and Management, Baden Baden, Germany.

Hung, H., E. Gedik and L. Cabrera-Quiros (2018). Complex Conversational Scene Analysis Using Wearable Sensing. Multi-modal Behavior Analysis in the Wild: Advances and Challenges.

Idrissou, A., R. Hoekstra, F. V. Harmelen, A. Khalili and P. V. D. Besselaar (2017). “Is my:sameAs the same as your:sameAs? Lenticular Lenses for Context Specific Identity.” Int. Conf. Knowledge Capture.

Johnson, M., J. M. Bradshaw, P. J. Feltovich, C. M. Jonker, M. B. Van Riemsdijk and M. Sierhuis (2014). “Coactive Design: Designing Support for Interdependence in Joint Activity.” J. of Human-Robot Interaction 3(1): 43-69.

Jonker, C. M., R. Aydoğan, T. Baarslag, J. Broekens, C. A. Detweiler, K. V. Hindriks, A. Huldtgren and W. Pasman (2017). An Introduction to the Pocket Negotiator: A General Purpose Negotiation Support System. Multi-Agent Systems and Agreement Technologies. EUMAS 2016, AT 2016. LNCS vol 10207.

Jonker, C. M., R. Aydogan, T. Baarslag, K. Fujita, T. Ito et al. (2017). Automated Negotiating Agents Competition. Proc. of the Thirty-First AAAI.

Jonker, C. M., M. B. van Riemsdijk and B. Vermeulen (2011). Shared mental models. Coordination, organizations, institutions, and norms in agent systems. Springer 6541: 132-151.

Jonker, C. M., J. L. Snoep, J. Treur, H. V. Westerhoff and W. C. A. Wijngaards (2010). “The Living Cell as a Multi-agent Organisation: A Compositional Organisation Model of Intracellular Dynamics.” Trans. on Computational Collective Intelligence 6220: 160-206.

Jonker, C. M. and J. Treur (2002). “Compositional verification of multi-agent systems: a formal analysis of pro-activeness and reactiveness.” Int. J. of Cooperative Information Systems 11: 51-91.

Jonker, C. M. and Treur, J (1997). Modelling an Agent’s Mind and Matter. Multi-Agent Rationality and 8th European Workshop on Modelling Autonomous Agents in a Multi- Agent World, Springer.

Kaptein, F., J. Broekens, K. Hindriks and M. Neerincx (2017). The role of emotion in self-explanations by cognitive agents. In Affective Computing and Intelligent Interaction Workshops and Demos: 88-93.

Koeman, V. J., K. V. Hindriks and C. M. Jonker (2017a). “Designing a source-level debugger for cognitive agent programs.” Autonomous Agents and Multi-Agent Systems 31: 941-970.

Koeman, V. J., K. V. Hindriks and C. M. Jonker (2017b). Omniscient Debugging for Cognitive Agent Programs. Proc. of the 26th Int. Joint Conf. on Artificial Intelligence.

Kotthoff, L., C. Thornton, H. H. Hoos and et al. (2017). “Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA.” J. Machine Learning Research 18: 1-25.

Kruijff-Korbayová, I., F. Colas, M. Gianni, F. Pirri, J. de Greeff, K. Hindriks, M. A. Neerincx, P. Ögren, T. Svoboda and R. Worst (2015). “TRADR project: Long-term human-robot teaming for robot assisted disaster response.” Artificial Intelligence 29(2): 193-201.

Looije, R., M. A. Neerincx and K. V. Hindriks (2017). “Specifying and testing the design rationale of social robots for behavior change in children.” Cognitive Systems Research 43: 250-265.

Mioch, T., M. Peeters and M. A. Neerincx (2018). Improving Adaptive Human-Robot Cooperation through Work Agreements. 27th IEEE Int. Symp. on Robot and Human Interactive Communication.

Mioch, T., N. Smets and M. A. Neerincx (2012). Predicting performance and situation awareness of robot operators in complex situations by unit task tests. 5th Int. Conf. on Advances in Computer-Human Interactions.

Neerincx, M. A., J. Van der Waa, F. Kaptein and J. Van Diggelen (2018). “Using perceptual and cognitive explanations for enhanced human-agent team performance.” EPCE LNAI 10906: 204–214.

Polevoy, G., M. de Weerdt and C. M. Jonker (2016). The Convergence of Reciprocation. Proc. of AAMAS.

Prakken, H. and G. Sartor (2015). “Law and logic: a review from an argumentation perspective.” Artificial Intelligence 227: 214-245.

Ren, Z., S. Liang, P. Li, S. Wang and M. de Rijke (2017). Social Collaborative Viewpoint Regression with Explainable Recommendations. Proc. of the Tenth ACM Int. Conf. on Web Search and Data Mining.

Romano, A. and D. Balliet (2017). “Reciprocity Outperforms Conformity to Promote Cooperation.” Psychological Science 28(10): 1490-1502.

Romano, A., D. Balliet and J. Wu (2017). “Unbounded indirect reciprocity: Is reputation-based cooperation bounded by group membership?” J. of Experiemental Social Psychology 71: 59-67.

Romano, A., D. Balliet, T. Yamagishi and J. H. Liu (2017). “Parochial trust and cooperation across 17 societies.” Proc Natl Acad Sci U S A 114(48): 12702-12707.

Schouten, D. G., F. Venneker, T. Bosse, M. A. Neerincx and A. H. Cremers (2018). “A digital coach that provides affective and social learning support to low-literate learners.” IEEE Trans. on Learning Technologies 11(1): 67-80.

Segers, R., T. Caselli and P. Vossen (2018). The Circumstantial Event Ontology (CEO) and ECB+/CEO; an Ontology and Corpus for Implicit Causal Relations between Events. Proc. of the Language Resources and Evaluation Conf.

Sharchilev, B., Y. Ustinovsky, P. Serdyukov and M. de Rijke (2018). Finding influential training samples for gradient boosted decision trees. Int. Conf. on Machine Learning

ter Hoeve, M., M. Heruer, D. Odijk, A. Schuth, M. Spitters and M. de Rijke (2017). Do News Consumers Want Explanations for Personalized News Rankings? FATREC Worksh. on Responsible Recommendation.

ter Hoeve, M., A. Schuth, D. Odijk, M. de Rijke(2018). “Faithfully explaining rankings in a news recommender system.” arXiv preprint arXiv:1805.05447.

Thornton, C., F. Hutter, H. H. Hoos and K. Leyton-Brown (2013). “Auto-WEKA: combined selection and hyperparameter optimization of classification algorithms.” Proc. KDD: 847-855.

Timmer, S., J.-J. C. Meyer, H. Prakken, S. Renooij and B. Verheij (2017). “A two-phase method for extracting explanatory arguments from Bayesian networks.” Int. J. of Approx, Reasoning 80: 475-494.

van der Waa, J., M. Robeer, J. van Diggelen, M. Brinkhuis and M. Neerincx “Contrastive Explanations with Local Foil Trees.” arXiv preprint arXiv:1806.07470.

van Doorn, J., D. Odijk, D. M. Roijers and M. de Rijke (2016). Balancing Relevance Criteria through Multi-Objective Optimization. Int. ACM SIGIR Conf. on Information Retrieval.

van Wissen, A., Y. A. Gal, B. A. Kamphorst and M. V. Dignum (2012). “Human–agent teamwork in dynamic environments.” Computers in Human Behavior 28(1): 23-33.

Verbrugge, R. and L. Mol (2008). “Learning to apply theory of mind.” J. of Logic, Language and Information 17(4): 489-511.

Verdiesen, I., V. Dignum and J. Van Den Hoven (2018). “Measuring Moral Acceptability in E-deliberation: A Practical Application of Ethics by Participation.” ACM Trans. Internet Technol. 18(4).

Verheij, B. (2017). “Proof With and Without Probabilities. Correct Evidential Reasoning with Presumptive Arguments, Coherent Hypotheses and Degrees of Uncertainty. .” Artificial Intelligence and Law 25(1): 127-154.

Verheij, B., F. Bex, S. Timmer, Vlek, Meyer, Renooij and H. Prakken (2016). “Arguments, scenarios and probabilities: connections between three normative frameworks for evidential reasoning.” Law, Probability and Risk 15: 35-70.

Vlek, C. S., H. Prakken and S. Renooij (2014). “Building Bayesian networks for legal evidence with narratives: a case study evaluation.” Artif Intell Law 22: 375.

Vlek, C. S., H. Prakken and S. Renooij (2016). “A method for explaining Bayesian networks for legal evidence with scenarios.” Artif Intell Law 24: 285.

Vossen, P., S. Baez, L. Bajčetić and B. Kraaijeveld (2018). “Leolani: a reference machine with a theory of mind for social communication.” Preprint

Vossen, P., M. Postma and F. Ilievski (2018). Don’t Annotate, but Validate: A Data-to-Text Method for Capturing Event Data. Proc. of the Language Resources and Evaluation Conf.

Wu, J., D. P. Balliet and P. A. M. van Lange (2016). “Reputation management: Why and how gossip enhances generosity.” Evolution and Human Behavior 37: 193-201.

Xu, J., J. Broekens, K. Hindriks and M. A. Neerincx (2014). Effects of bodily mood expression of a robotic teacher on students. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems: 2614-2620.

Xu, J., J. Broekens, K. Hindriks and M. A. Neerincx (2015). Effects of a robotic storyteller’s moody gestures on storytelling perception. Int. Conf. on Affective Computing and Intelligent Interaction.

Xu, J., J. Broekens, K. Hindriks and M. A. Neerincx (2015). “Mood contagion of robot body language in human robot interaction.” Autonomous Agents and Multi-Agent Systems 29(6): 1216–1248.