Workshop Description

Reasoning is a core ability in human cognition. Its power lies in the ability to theorize about the environment, to make implicit knowledge explicit, to generalize given knowledge and to gain new insights. There are a lot of findings in cognitive science research which are based on experimental data about reasoning tasks, among others models for the Wason selection task or the suppression task discussed by Byrne and others. This research is supported also by brain researchers, who aim at localizing reasoning processes within the brain. Early work starting with often used propositional logic as a normative framework. Any deviation from it has been considered an error. Central results like findings from the Wason selection task or the suppression task inspired a shift from propositional logic and the assumption of monotonicity in human reasoning towards other reasoning approaches. This includes but is not limited to models using probabilistic approaches, mental models, or non-monotonic logics. Considering cognitive theories for syllogistic reasoning show that none of the existing theories is close to the existing data. But some formally inspired cognitive complexity measures can predict human reasoning difficulty for instance in spatial relational reasoning. Automated deduction, on the other hand, is mainly focusing on the automated proof search in logical calculi. And indeed there is tremendous success during the last decades. Recently a coupling of the areas of cognitive science and automated reasoning is addressed in several approaches. For example there is increasing interest in modeling human reasoning within automated reasoning systems including modeling with answer set programming, deontic logic or abductive logic programming. There are also various approaches within AI research for common sense reasoning and in the meantime there even exist benchmarks for commonsense reasoning, like the Winograd and the Choice of Plausible Alternatives (COPA) challenge. Despite a common research interest -- reasoning -- there are still several milestones necessary to foster a better inter-disciplinary research. First, to develop a better understanding of methods, techniques, and approaches applied in both research fields. Second, to have a synopsis of the relevant state-of-the-art in both research directions. Third, to combine methods and techniques from both fields and find synergies. E.g., techniques and methods from computational logic have never been directly applied to model adequately human reasoning. They have always been adapted and changed. Fourth, we need more and better experimental data that can be used as a benchmark system. Fifth, cognitive theories can benefit from a computational modeling. Hence, both fields -- human and automated reasoning -- can both contribute to these milestones and are in fact a conditio sine qua non. Achievements in both fields can inform the others. Deviations between fields can inspire to seek a new and profound understanding of the nature of reasoning. This is the fourth workshop in a series of successful Bridging workshops located at previous conferences: 2015 at the International Conference on Automated Deduction in Berlin (CADE-25), 2016 at the International Conference on Artificial Intelligence in New York (IJCAI 2016), 2017 at the Annual Meeting of the Cognitive Science Society. The goal of this workshop is to bring together leading researchers from artificial intelligence, automated deduction, computational logics and the psychology of reasoning that are interested in a computational foundations of human reasoning -- both as speakers and as audience members. Its ultimate goal is to share knowledge, discuss open research questions, and inspire new paths. Like its preceding event, it is intended to get an overview of existing approaches and make a step towards a cooperation between computational logic and cognitive science. Topics of interest include, but are not limited to the following:
  • benchmark problems relevant in both fields
  • approaches to tackle Benchmark problems like the Winograd Schema Challenge or the COPA challenge
  • limits and differences between automated and human reasoning,
  • psychology of deduction,
  • common sense reasoning,
  • logics modeling human cognition,
  • modeling human reasoning using automated reasoning systems and
  • non-monotonic, defeasible, and classical reasoning and possible explanations for human reasoning.
  • The call for papers can be found here. The workshop is part of the FAIM workshop program located at the Federated Artificial Intelligence Meeting (FAIM) which includes the major conferences IJCAI-ECAI , ICML, AAMAS, ICCBR and SoCS. The Bridging workshop is supported by IFIP TC12.

    List of important dates

  • Full Paper submission deadline: 2nd of May, 2018
  • Notification: 28th of May, 2018
  • Workshop: 14th of July, 2018
  • Submission and Contribution Format

    Papers, including the description of work in progress are welcome and should be formatted according to IJCAI guidelines. The length should not exceed 6 pages excluding references. All papers must be submitted in PDF. Formatting instructions and the style files can be obtained here. The EasyChair submission site is available at:


    Most likely, proceedings of the workshop will be published as CEUR workshop proceedings.


  • Ulrich Furbach, University of Koblenz
  • Sangeet Khemlani, Naval Research Laboratory, Washington DC
  • Oliver Obst, Western Sydney University
  • Marco Ragni, University of Freiburg
  • Claudia Schon, University of Koblenz
  • Contact: Claudia Schon
  • Program Committee

  • Emmanuelle Diez Saldanha, University of Dresden
  • Ulrich Furbach, University of Koblenz
  • Steffen Hölldobler, University of Dresden
  • Antonis C. Kakas, University Cyprus, Cyprus
  • Gabriele Kern-Isberner, TU Dortmund
  • Sangeet Khemlani, Naval Research Lab, USA
  • Robert A. Kowalski, Imperial College London, GB
  • Ursula Martin, University of Oxford
  • Oliver Obst, Western Sydney University
  • Luís Moniz Pereira, Universidade Nova Lisboa, Portugal
  • Marco Ragni, University of Freiburg
  • Claudia Schon, University of Koblenz
  • Frieder Stolzenburg, Harz University of Applied Sciences
  • Contact: Claudia Schon

    Accepted Papers

    Larry Moss and Charlotte Raty, Reasoning About the Sizes of Sets: Progress, Problems and Prospects

    Marcos Cramer and Mathieu Guillaume, Directionality of Attacks in Natural Language Argumentation

    Stefania Costantini, Abeer Dyoub and Valentina Pitoni, Reflection and Introspection for Humanized Intelligent Agents

    Andrew Fish, Alexei Lisitsa and Alexei Vernitski, Towards human readability of automated unknottedness proofs

    Alison Pease and Ursula Martin, "Human-like" example-use in mathematical research

    Sjur Kristoffer Dyrkolbotn and Truls Pedersen, A formal analysis of enthymematic arguments