Tavarua, Fiji; credit: Tourism Fiji

Knowledge Representation Conventicle

26th and 27th of August 2019

Yanuca, Fidji



The event will consist in one workshop (6 invited talks) and two half-day tutorials.

Workshop: Foundations of belief change

The problem of belief change---the problem of how an intelligent agent should update their qualitative beliefs in response to new information---is a crucial issue in knowledge representation. It bears deep formal and conceptual connections to a number of AI subdisciplines, including nonmonotonic reasoning and belief merging, as well as social choice.

The past three decades have seen the emergence of a substantial and sophisticated body of work on this problem, engaging researchers from a variety of disciplines, including artificial intelligence, logic and philosophy.

The present workshop will focus on foundational issues pertaining to the axiomatic models that have been developed in this context. Possible topics include, for instance:

  • Connections between qualitative and quantitative models of belief change
  • Parallels and discrepancies between belief change and preference change
  • Connections between belief change and social choice
  • Learning-theoretic aspects of belief revision
  • Weakenings or strengthenings of common postulates for belief change
  • Connections between belief change and nonmonotonic logics

Talks will include both original contributions and brief topical surveys.

Tutorial 1: Iterated Belief Change (presented by Jake Chandler, co-authored with Richard Booth, Cardiff University, UK)

The problem of belief change--the problem of how an intelligent agent should update their belief state in response to new information--is a crucial issue in knowledge representation. It bears deep formal and conceptual connections to a number of AI subdisciplines, including nonmonotonic reasoning and belief merging, as well as social choice.

A substantial and sophisticated literature on this topic has emerged over the past two to three decades, spanning a number of disciplines. In spite of this, there remains widespread disagreement on one of the most fundamental aspects of the core model. Indeed, while the rationality constraints operating on single changes in view have long been well understood, the nature of the principles governing the outcome of a succession of such changes--so-called iterated change--remains surprisingly very much up for grabs. This tutorial provides an up-to-date and systematic survey of work on this vexed question, doubling up as an introduction to the study of belief change more generally.

Projected topics:

  1. Single-shot Belief Change (AGM postulates; representation with total-preorders; conditional beliefs and rational consequence; Levi and Harper Identities)
  2. Iterated revision I: background (Darwiche-Pearl postulates; Booth & Meyer's principle (P); reductionist proposals; criticisms of Darwiche-Pearl and reductionism)
  3. Iterated revision II: enriched states (various approaches to non-prioritised revision; prioritised revision with ordinal intervals and ranking functions)
  4. Iterated contraction I: background (postulates of Chopra et al; reductionist proposals; iterated versions of the Levi and Harper Identities)
  5. Iterated contraction II: enriched states (contraction with ordinal intervals and ranking functions)
  6. Iterated change in conditional beliefs (Kern-Isberner postulates; other related work)

This tutorial will be a repeat of a tutorial given at IJCAI2019, two weeks prior, in Macau. See here.

Tutorial 2: Cognitive Logics: Formal and Cognitive Methods for Reasoning in a Dynamic World (presented by Gabriele Kern-Isberner and Marco Ragni)

Systems and methods for Artificial Intelligence (AI) applicable in the real world require to represent and reason about uncertain knowledge. While this is a limitation of classical first-order logic, there is a large number of so-called non-monotonic logics, i.e., logics that aim to draw inferences only cautiously, allowing for revising them if new information becomes available. Cognitive analysis have shown that human inferential behavior can be better described employing such logics. In this tutorial we introduce the cognitive and formal foundations of cognitive logics, relevant benchmark problems, and challenges in modeling cognitive reasoning.

Projected topics:

  1. What is the right logic for human reasoning in AI? -- Classical fallacies
  2. Formal models of commonsense reasoning (Reiter's default logic; logic programming and weak completion semantics; conditionals and ranking functions: system Z and c-representations)
  3. Cognitive aspects of Cognitive Logics (Cognitive theories and principles, psychological benchmark examples; Cognitive modeling of human reasoning, especially of conditional and syllogistic reasoning; Logical incorrectness of human reasoning and how to escape irrationality; the role of background knowledge in psychological experiments)
  4. Formal and cognitive mechanisms of belief revision
  5. Discussion



Jim Delgrande, Professor, School of Computing Science, Simon Frazer University, Canada

Eduardo Fermé, Associate Professor, Faculty of Exact Sciences and Engineering, University of Madeira, Portugal

Nina Gierarsimzuk, Associate Professor, Department of Applied Mathematics and Computer Science, Danish Technical University, Denmark

Gabriele Kern-Isberner, Professor, Faculty of Informatics, Technical University of Dortmund, Germany

Pavlos Peppas, Professor, Department of Business Administration, University of Patras, Greece

Kai Sauerwald, PhD Candidate, Faculty of Mathematics and Informatics, University of Hagen, Germany

Ted Shear, Postdoctoral Research Fellow, School of Economics, University of Queensland, Australia

Marco Ragni, Associate Professor, Institute for Informatics, University of Freiburg, Germany



Jake Chandler, Senior Lecturer and ARC Future Fellow, Department of Computer Science and IT, La Trobe University, Australia

Michael Thielscher, Professor, School of Computer Science and Engineering, University of New South Wales, Australia




8:45-9:00 Welcome

9:00-10:30 Tutorial 1: Iterated Belief Change

10:30-11:00 Coffee break

11:00-12:30 Tutorial 1: Iterated Belief Change

12:30-14:00 Lunch break

14:00-15:00 Workshop talk 1

15:00-15:30 Coffee break

15:30-16:30 Workshop talk 2

16:30-17:30 Workshop talk 3

19:30-late Workshop dinner & drinks


9:00-10:30 Tutorial 2: Cognitive Logics

10:30-11:00 Coffee break

11:00-12:30 Tutorial 2: Cognitive Logics

12:30-14:00 Lunch break

14:00-15:00 Workshop talk 4

15:00-15:30 Coffee break

15:30-16:30 Workshop talk 5

16:30-17:30 Workshop talk 6



The KR Conventicle is a gathering of Australian researchers and their friends and colleagues from overseas working on all aspects of Knowledge Representation and Reasoning (KRR) and related disciplines. KR Conventicles have been organised sporadically, typically aligned with a visit to Australia by a sizeable number of distinguished KR researchers. The purpose of the conventicle is to present latest results and current research in the wider field of KR, to discuss about past and future research directions, and to establish network with like-minded colleagues.

Past conventicles have been held at Macquarie University (2002, 2008) and UNSW (2011, 2016).



This workshop is generously funded by La Trobe University, in the context of an Australian Research Council Future Fellowship (project number FT160100092), awarded to Jake Chandler.



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  • Full Paper Submission Due: March 15, 2019
  • Tutorial & Workshop Due: April 20, 2019
  • Acceptance Notification: May 31, 2019 June 3, 2019
  • Camera-Ready Papers Due: Jun 15, 2019
  • Conference: Aug 26-30, 2019

Supporting Organisations




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