Peer reviewed journal papers

Johan Kwisthout, Bill Phillips, Anil Seth, Iris van Rooij, and Andy Clark (2017). Editorial to the special issue on perspectives on human probabilistic inference and the 'Bayesian brain'.Brain and Cognition, 112, 1-2.(preprint) Johan Kwisthout, Harold Bekkering, and Iris van Rooij (2017). To be precise, the details don't matter: On predictive processing, precision, and level of detail of predictions.Brain and Cognition, 112, 84-91.(preprint) Stan van Pelt, Lieke Heil, Johan Kwisthout, Sasha Ondobaka, Iris van Rooij, and Harold Bekkering (2016). Beta- and gamma activity reflect predictive coding in the processing of causal events.Social Cognitive and Affective Neuroscience, 11(6), 973-980.(no preprint yet) Johan Kwisthoutand Iris van Rooij (2015). Free energy minimization and information gain: The devil is in the details. Commentary on Friston, K., Rigoli, F., Ognibene, D., Mathys, C., FitzGerald, T., and Pezzulo, G. (2015). Active Inference and epistemic value.Cognitive Neuroscience, 6(4), 216-218.(preprint) Johan Kwisthout(2015). Tree-Width and the Computational Complexity of MAP Approximations in Bayesian Networks.Journal of Artificial Intelligence Research, 53, 699-720.(preprint) Johan Kwisthout(2015). Most Frugal Explanations in Bayesian Networks.Artificial Intelligence, 218, 56 - 73.(preprint) Iris van Rooij, Cory D. Wright, Johan Kwisthout, and Todd Wareham (2014). Rational analysis, intractability, and the prospects of 'as if'-explanations.Synthese(DOI: 10.1007/s11229-014-0532-0).(no preprint yet) Maria Otworowska, Johan Kwisthout, and Iris van Rooij (2014). Counter-factual mathematics of counterfactual predictive models.Frontiers in Consciousness Research, 5 (801).Lieke Heil, Stan van Pelt, Johan Kwisthout, Iris van Rooij, and Harold Bekkering (2013). Higher-level processes in the formation and application of associations during action understanding. Commentary to: Cook, Bird, Catmur, Press, and Heyes (2014). Mirror neurons: From origin to function.Behavioral and Brain Sciences, 37(2), 202 - 203.(no preprint yet) Mark Blokpoel, Johan Kwisthout, Theo P. van der Weide, Todd Wareham, and Iris van Rooij (2013). A Computational-level Explanation of the Speed of Goal Inference.Journal of Mathematical Psychology, 57(3-4), 117 - 133.(no preprint yet) Johan Kwisthoutand Iris van Rooij (2013). Bridging the Gap between Theory and Practice of Approximate Bayesian Inference.Cognitive Systems Research, 24, 2 - 8.

(preprint) Mark Blokpoel, Johan Kwisthout, and Iris van Rooij (2012). When can predictive brains be truly Bayesian? Commentary to: Clark (2013). Whatever next? Neural prediction, situated agents, and the future of cognitive science.Frontiers in Theoretical and Philosophical Psychology, 3 (406).Johan Kwisthout(2012). Relevancy in Problem Solving: A Computational Framework.Journal of Problem Solving, 5 (1), 18 - 33.Johan Kwisthout(2011). Most Probable Explanations in Bayesian Networks: Complexity and Tractability.International Journal of Approximate Reasoning, 52 (9), 1452 - 1469.(preprint) Iris van Rooij, Johan Kwisthout, Mark Blokpoel, Jakub Szymanik, Todd Wareham, and Ivan Toni (2011). Intentional communication: Computationally Easy or Difficult?Frontiers in Human Neuroscience, 5 (52), 1 - 18.Johan Kwisthout, Todd Wareham, and Iris van Rooij (2011). Bayesian Intractability is not an Ailment that Approximation can Cure.Cognitive Science, 35 (5), 779 - 784.(preprint) Johan Kwisthoutand Gerard Tel (2008). Complexity Results for Enhanced Qualitative Probabilistic Networks.International Journal of Approximate Reasoning, 48 (3), 879 - 888.(preprint) Johan Kwisthout, Paul Vogt, Pim Haselager and Ton Dijkstra (2008). Joint Attention and Language Evolution.Connection Science, 20 (2-3), 155 - 171.(preprint)

Peer reviewed conference papers with published proceedings

Johan Kwisthout(2016).What can the PGM community contribute to the 'Bayesian Brain'?. In T. Bosse and B. Bredeweg (Eds.): Proceedings of the 28th Benelux Conference on AI (BNAIC'16), November 10-11, Amsterdam, Netherlands.Johan Kwisthout(2016).The Parameterized Complexity of Approximate Inference in Bayesian Networks. In A. Antonucci, G. Corani, and C.P. de Campos (Eds.): Proceedings of the Eighth International Conference on Probabilistic Graphical Models (PGM'16), September 5-9, Lugano, Switzerland. Proceedings of Machine Learning Research, 52, pp. 264-274.Maria Otoworowska, Jordi Riemens, Chris Kamphuis, Pieter Wolfert, Louis Vuurpijl, and Johan Kwisthout(2015).The Robo-havioral Methodology: Developing Neuroscience Theories with FOES. Proceedings of the 27th Benelux Conference on AI (BNAIC'15), November 5-6, Hasselt, Belgium.Johan Kwisthout(2014).Treewidth and the Computational Complexity of MAP Approximations. In van der Gaag, Linda C., Feelders, Ad J. (Eds.): Proceedings of the Seventh European Workshop on Probabilistic Graphical Models (PGM'14), September 17-19, Utrecht, Netherlands. Springer LNAI 8754. pp. 271-285.(preprint) Johan Kwisthout(2014).Minimizing relative entropy in Hierarchical Predictive Coding. In van der Gaag, Linda C., Feelders, Ad J. (Eds.): Proceedings of the Seventh European Workshop on Probabilistic Graphical Models (PGM'14), September 17-19, Utrecht, Netherlands. Springer LNAI 8754. pp. 254-270.(preprint) Johan Kwisthout(2013).Most Frugal Explanations: Occam's Razor Applied to Bayesian Abduction. In K. Hindriks, M. de Weerdt, B. van Riemsdijk, and M. Warnier (Eds.): Proceedings of the 25th Benelux Conference on AI (BNAIC'13), November 7-8, 2013, Delft, Netherlands. pp. 96-103.Johan Kwisthout(2013).Structure Approximation of Most Probable Explanations in Bayesian Networks. In L.C. van der Gaag (Ed.): Proceedings of the 12th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU'13), July 7-10, 2013, Utrecht, The Netherlands. Springer LNAI 7958, pp. 340-351.(preprint) Johan Kwisthout(2013).Most Inforbable Explanations: Finding Explanations in Bayesian Networks that are both Probable and Informative. In L.C. van der Gaag (Ed.): Proceedings of the 12th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU'13), July 7-10, 2013, Utrecht, The Netherlands. Springer LNAI 7958, pp. 328-339.(preprint) Johan Kwisthout(2012).Structure Approximation of Most Probable Explanations in Bayesian Networks. In J.W.H.M. Uiterwijk, N. Roos, and M.H.M. Winands (Eds.): Proceedings the 24th Benelux Conference on AI (BNAIC'12), October 25-26, 2012, Maastricht, The Netherlands. pp. 131-138.Johan Kwisthoutand Iris van Rooij (2012).Bridging the Gap between Theory and Practice of Approximate Bayesian Inference. In N. Rußwinkel, U. Drewitz, and H. van Rijn (Eds.): Proceedings of the 11th International Conference on Cognitive Modeling (ICCM'12), April 16-19, 2012, Berlin, pp. 199-204.Johan Kwisthoutand Peter Lucas (2011).Reasoning With Different Time Granularities in Industrial Applications: A Case Study Using CP-logic.In P. De Causmaecker, J. Maervoet, T. Messelis, K. Verbeeck, and T. Vermeulen (Eds.): Proceedings of the 23rd Benelux Conference on AI (BNAIC'11), November 3-4, 2011, Ghent, Belgium, pp. 120 - 127.Todd Wareham, Johan Kwisthout, Pim Haselager and Iris van Rooij (2011).Ignorance is Bliss: A Complexity Perspective on Adapting Reactive Architectures.Proceedings of the First IEEE Conference on Development and Learning and on Epiginetic Robotics, August 24-27, 2011, Frankfurt am Main, Germany, pp. 465 - 470.(preprint) Mark Blokpoel, Johan Kwisthout, Todd Wareham, Pim Haselager, Ivan Toni, and Iris van Rooij (2011).The computational costs of recipient design and intention recognition in communication. In L. Carlson, C. Hoelscher, and T.F. Shipley (Eds.): Proceedings of the 33rd Annual Meeting of the Cognitive Science Society (CogSci'11), July 20-23, 2011, Boston, Massachusetts, pp. 465 - 470. See also supplementary materialJohan Kwisthout, Hans Bodlaender, and Linda van der Gaag (2011).The Complexity of Finding kth Most Probable Explanations in Probabilistic Networks. In I. Cerná, T. Gyimóthy, J. Hromkovic, K. Jefferey, R. Královic, M. Vukolic and S. Wolf (Eds.): Proceedings of the 37th International Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM'11), January 22-28, 2011, Novy Smokovec, Slovakia. Springer LNCS 6543, pp. 356 - 367(preprint) Johan Kwisthout(2010).Two New Notions of Abduction in Bayesian Networks. In P. Bouvry et al. (Eds.): Proceedings of the 22nd Benelux Conference on AI (BNAIC'10), October 25-26, Luxembourg, pp. 82-89.Johan Kwisthout, Hans Bodlaender, and Linda van der Gaag (2010).The Necessity of Bounded Treewidth for Efficient Inference in Bayesian Networks. In H. Coelho, R. Studer, M. Wooldridge (Eds.): Proceedings of the 19th European Conference on Artificial Intelligence (ECAI'10), August 16-20, Lisbon, Portugal. IOS Press, pp. 237-242.Mark Blokpoel, Johan Kwisthout, Theo van der Weide and Iris van Rooij (2010).How Action Understanding can be Rational, BayesianandTractable. In S. Ohlsson and R. Catrambone (Eds.): Proceedings of the 32th Annual Meeting of the Cognitive Science Society (CogSci'10), August 11-14, Portland, Oregon, pp. 1643-1648. See also supplementary material.Johan Kwisthout(2008).Complexity Results for Enumerating MPE and Partial MAP. In M. Jaeger and T. Nielsen (Eds.): Proceedings of the Fourth European Workshop on Probabilistic Graphical Models (PGM'08), September 17-19, 2008, Hirthals, Denmark. pp 161-168.Johan Kwisthoutand Linda van der Gaag (2008).The Computational Complexity of Sensitivity Analysis and Parameter Tuning. In D. McAllester and P. Myllymaki (Eds.): Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence (UAI'08), July 9-12, 2008, Helsinki, Finland. UAI press, pp. 349-356.Johan Kwisthout, Hans Bodlaender, and Gerard Tel (2007).Local Monotonicity in Probabilistic Networks. In K. Mellouli (Ed.): Proceedings of the Ninth European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU'07), October 31-November 2, 2007, Hammamet, Tunisia. Springer LNAI 4724, pp. 548 - 559.(preprint) Johan Kwisthout(2007).The Computational Complexity of Monotonicity in Probabilistic Networks. In E. Csuhaj-Varj and Z. Esik (Eds.): Proceedings of the Sixteenth International Symposium on Fundamentals of Computation Theory (FCT'07), August 27-30, 2007, Budapest, Hungary. Springer LNCS 4639, pp. 388 - 399.(preprint) Johan Kwisthoutand Gerard Tel (2006).Complexity Results for Enhanced Qualitative Probabilistic Networks. In M. Studeny and J. Vomlel (Eds.): Proceedings of the Third European Workshop on Probabilistic Graphical Models (PGM'06), September 12-15, 2006, Prague, Czech Republic, pp. 171 - 178.Johan Kwisthoutand Mehdi Dastani.Modelling Uncertainty in Agent Programming. In M. Baldoni, U. Endriss, A. Omicini, and P. Torroni (Eds.): Proceedings of the Third International Workshop on Declarative Agent Languages and Technologies (DALT'05), July 25, 2005, Utrecht, The Netherlands. Springer LNCS 3904, pp. 17 - 32.(preprint)

(Edited) books

Franc Grootjen, Maria Otworowska, and Johan Kwisthout(2014). Proceedings of the 26th Benelux Conference on AI (BNAIC'14), November 6-7, Nijmegen(BNAIC 2014 website) Iris van Rooij, Johan Kwisthout, and Todd Wareham (in prep). Cognition and Intractability: A Guide to Classical and Parameterized Complexity Analysis. To appear with Cambridge University Press, 2016.

Posters, (extended) abstracts, technical reports, and other publications

Ezgi Kayhan, Lieke Heil,Johan Kwisthout, Iris van Rooij, Sabine Hunnius, and Harold Bekkering (accepted). Young Children Integrate Current Observations, Priors and Agent Information to Build Predictive Models of Others' Actions.Accepted for poster presentation at the 2017 SRCD, Austin, the United States.

Stan van Pelt, Lieke Heil,Johan Kwisthout, Iris van Rooij, and Harold Bekkering. Oscillatory correlates of the use of world knowledge in predictive models for the perception of causal events.Poster presentation at BioMAG 2016.

Maria Otworowska, Lorijn Zaadnoordijk, Erwin de Wolff,Johan Kwisthout, and Iris van Rooij. Causal learning in the crib: A predictive processing formalisation and babybot simulation.Poster presentation at ICDL/EpiRob 2016.Shared best poster award!

Lorijn Zaadnoordijk, Maria Otworowska,Johan Kwisthout, Sabine Hunnius, and Iris van Rooij. The mobile-paradigm as measure of infants' sense of agency? Insights from babybot simulations.Accepted (poster presentation) to ICDL/EpiRob 2016.Shared best poster award!

Maria Otworowska, Lorijn Zaadnoordijk, Erwin de Wolff,Johan Kwisthout, and Iris van Rooij. Causal learning in the crib: a predictive processing formalisation and babybot simulation.Oral presentation at the 2016 meeting of the European Mathematical Psychology Group.

Sarit Pink-Hashkes andJohan Kwisthout. Perception is in the details: A predictive coding account of the effects of 5-Hydroxytryptamine 2A (5-HT2A) agonists.Oral presentation at the 2016 Interdisciplinary Conference on Psychedelics Research. Lorijn Zaadnoordijk, Sabine Hunnius, Marlene Mayer,Johan Kwisthout, and Iris van Rooij. What senses of agency can infants have?Poster presentation at CogSci 2015.

Lorijn Zaadnoordijk, Sabine Hunnius, Marlene Meyer,Johan Kwisthout, and Iris van Rooij. The developing sense of agency: An interdisciplinary challenge.Poster presentation at ICDL/EpiRob 2015.

Ezgi Kayhan, Lieke Heil,Johan Kwisthout, Iris van Rooij, Sabine Hunnius, and Harold Bekkering. What's Next?: Young Children Integrate Prior Probability Information With New Observations to Predict Others' Actions.Poster presentation at SRCD 2015.

Johan Kwisthout, Harold Bekkering, and Iris van Rooij (2015). To be precise, the details don't matter: On predictive processing, precision, and level of detail of predictions. Poster presentation at CNS 2015.

Stan van Pelt, Lieke Heil, Sasha Ondobaka,Johan Kwisthout, Iris van Rooij, and Harold Bekkering (2014). Neuromagnetic Correlates of Action Probabilities at Different Hierarchical Levels. Poster presentation at Biomag 2014.

Ezgi Kayhan, Lieke Heil,Johan Kwisthout, Iris van Rooij, Sabine Hunnius, and Harold Bekkering (2014). Action prediction based on priors and observations. Poster presentation at the ICIS 2014 pre-conference Action Development: Theory and Methods, Berlin, Germany.

Johan Kwisthout, Maria Otworowska, Harold Bekkering, and Iris van Rooij (2014). Leaving Andy Clark's safe shores: Scaling Predictive Processing to higher cognition. Poster presentation at CogSci 2014.

Johan Kwisthoutand Iris van Rooij (2013).Parameterized Complexity and Bayesian Models. Column in the September 2013 Newsletter of the Parameterized Complexity.

Johan Kwisthoutand Iris van Rooij (2013).Predictive Coding: Intractability Hurdles are Yet to Overcome. Presented (poster presentation) at CogSci 2013. See also supplementary material.

Johan Kwisthout(2011).A Formal Theory of Relevancy in Problem Solving. Technical report: ICIS-0R11005.

Johan Kwisthout(2011).The Computational Complexity of Probabilistic Inference. Technical Report ICIS--R11003.

Johan Kwisthout(2010).Two new notions of abduction in Bayesian networks.Technical Report ICIS--R10005.

Johan Kwisthout(2010).The year we make contact. Review of Arthur C. Clarke's2010, written for AI student magazineDe Connectie.

Johan Kwisthout(2010).Most Probable Explanations in Bayesian Networks: complexity and tractability.Technical Report ICIS--R10001.

Johan Kwisthoutand Hans Bodlaender (2009).Conditional Lower Bounds on the Complexity of Probabilistic Inference. Technical report UU-CS-2009-018.

Johan Kwisthout, Hans Bodlaender, and Gerard Tel (2007).Complexity Results for Local Monotonicity in Probabilistic Networks. Technical report UU-CS-2007-050.

Johan Kwisthout(2007).The Computational Complexity of Monotonicity in Probabilistic Networks. Technical report UU-CS-2007-040.

Johan Kwisthout, Paul Vogt, Pim Haselager and Ton Dijkstra (2007).Joint Attention and Language Evolution. Technical report UU-CS-2007-039.

Johan Kwisthout, Hans Bodlaender, and Gerard Tel (2007).Local Monotonicity in Probabilistic Networks(extended abstract). In M.M. Dastani & E. de Jong (Eds.): Proceedings of the 19th Belgium-Netherlands Conference on AI (BNAIC'07), October 17-19, 2007, Utrecht, The Netherlands pp. 369 - 370.

Johan Kwisthoutand Gerard Tel (2006).Complexity Results for Enhanced Qualitative Probabilistic Networks, Technical report UU-CS-2006-058.

Johan Kwisthoutand Mehdi Dastani.Modelling Uncertainty in Agent Programming(extended abstract). In K. Verbeeck, K. Tuyls, a. Nowé, B. Manderick, and B. Kuijpers (Eds.): Proceedings of the 17th Belgium-Netherlands Conference on AI (BNAIC'05), October 17-18, 2005, Brussels, Belgium, pp. 361 - 362.

Manuscripts

Lieke Heil,Johan Kwisthout, Stan van Pelt, Iris van Rooij, and Harold Bekkering. One wouldn't expect an expert bowler to hit only two pins: Hierarchical predictive processing of agent-caused events.Resubmitted after review.

Arastoo Bozorgi, Saeed Samet,Johan Kwisthout, and Todd Wareham. Community-based influence maximization in social networks under a competitive linear threshold model.Resubmitted after review.

Johan Kwisthoutand Iris van Rooij. Predictive processing and the Bayesian brain: Intractability hurdles that are yet to overcome.Submitted.

Johan Kwisthout. The parameterized complexity of approximate inference in Bayesian networks.Submitted.

Lorijn Zaadnoordijk, Maria Otworowska,Johan Kwisthout, Sabine Hunnius, and Iris van Rooij. Moving towards a sense of agency: Insights from babybot simulations of the mobile-paradigm.Submitted.

Ezgi Kayhan, Lieke Heil,Johan Kwisthout, Iris van Rooij, Sabine Hunnius, and Harold Bekkering. Young children integrate prior probabilities and current observations to build predictive models of others' actions.Submitted.

Sarit Hashkes-Pink, Iris van Rooij, andJohan Kwisthout. Perception is in the details: A predictive coding account of the psychedelic phenomenon.Submitted.

Fixed-error randomized tractability, Algorithms and Complexity Colloquium, University of Utrecht, April 25th, 2017.

To be precise, the details don't matter: On predictive processing, precision, and level of detail of predictions, IILC workshop 'How does predictive processing translate to abstract computational cognitive models', University of Amsterdam, March 21st 2017.

Learning generative models in Predictive Processing, ICDL/Epirob workshop Predictive Processing and Infant Development: The Current State-of-the-art, September 19th 2016.

Parameterized complexity theory: An indispensable tool for the cognitive (neuro)scientist, Donders Summerschool on Neurocomputational Approaches to Decision Making, Donders Institute, August 14th 2015.

Predictive Processing: A Conceptual Primer, Mini-Symposium on Predictive Processing and Autism Spectrum Conditions, Donders Institute, June 25th 2015.

A complexity-theoretic perspective on approximate Bayesian inferences, Modeling Minds workshop, April 23rd-24th 2015.

Most Frugal Explanations in Bayesian Networks, Computer Science Colloquium, University of Utrecht, November 14th 2014; Good AIfternoon Meeting, Radboud University Nijmegen, November 25th 2014.

Leaving Andy Clark's safe shores: Scaling Predictive Processing to higher cognition, Symposium on Predictions from the Neural Circuits to Theory of Mind, Donders Center for Cognition, May 19th 2014.

A complexity-theoretic perspective on the preconditions for Bayesian tractability, Lorentz Workshop on Human Probabilistic Inferences, Lorentz Center, Leiden, May 15th 2014.

Intractable Bayesian Models and Approximation: Neither Placebo nor Panacea, Models and Mechanisms Workshop, Tilburg University, December 7th 2012.

Parameterized Complexity Analysis - A New and Powerful Tool in the Cognitive Scientist's Toolbox, Department of Knowledge Engineering, Maastricht University, March 7th 2012.

Relevant Representations, Dagstuhl Seminar on Problem Solving: New Foundations, August 30th 2011.

Bayesian abduction in Cognitive Science, Good AIfternoon colloquium, Donders Institute, Nijmegen, June 20th 2011.

The Computational Complexity of Probabilistic Networks, Research Seminar Logic and Automata, RWTH Aachen, March 12th 2009.

Beyond NP: the complexity of uncertainty, IPA Herfstdagen, Deurne, November 29th 2007.

The Necessity of Joint Attention for Language Evolution, BNAIS Symposium, Nijmegen, June 2nd 2006.

The Necessity of Joint Attention for Language Evolution, poster presentation, CogSys II conference, Nijmegen, April 12th-13nd 2006.