Submissions

In accordance with the previous conferences, the proceedings of ECSQARU 2021 will be published in the Springer LNCS/LNAI Lecture Notes in Artificial Intelligence series. Authors are requested to prepare their conference papers in the LNCS/LNAI format - please, follow Springer Instruction for authors. Submitted papers must be original and not under review in a journal or another venue with formally published proceedings. They will be evaluated by peer reviews based on originality, significance, technical soundness, and clarity of exposition. Authors of accepted papers are expected to attend the conference to present their work, at least one author of each paper must register for the conference.

Please read the following instructions carefully:

  1. authors should prepare their conference papers in the LNCS/LNAI format - please use Springer LaTeX template or MS Word template. You may be also interested in using Overleaf where respective templates are also available. LNCS/LNAI Overleaf templates
  2. papers must not exceed 12 pages, excluding references;
  3. the submissions are not blind and they should mention authors and affiliations
  4. papers must be submitted electronically through Easychair; EasyChair
  5. Do not forget to attach a signed Consent to Publish required by Springer for publishing in Lecture Notes in Computer Sciences series with your final version submission.

Papers that are not in the stated format or that exceed the page limit will not be reviewed.

IJAR Extended versions of selected papers will be published in a special issue of International Journal of Approximate Reasoning published by Elsevier.

Scope

Scope

For ECSQARU 2021 we invite submissions of original papers on topics which include but are not limited to:

Algorithms for uncertain inference
Applications of uncertain systems
Argumentation systems
Automated planning and acting under uncertainty
Bayesian networks
Belief functions
Belief change & merging
Classification & clustering
Decision theory & decision graphs

Default reasoning
Description logics with uncertainty
Foundations of reasoning under uncertainty
Fuzzy sets & fuzzy logic
Game theory
Hybrid Reasoning
Imprecise probabilities
Inconsistency handling
Information fusion
Learning for uncertainty formalisms

Logics for reasoning under uncertainty
Markov decision processes
Possibility theory & possibilistic logic
Preferences
Probabilistic graphical models
Probabilistic logics
Qualitative uncertainty models
Rough sets
Uncertainty & data