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The Program Committee of the 34th Brazilian Conference on Intelligent
Systems (BRACIS) invites submissions of original research papers for the
conference to be held in Belém, PA, Brazil. **First edition in the North
Region**  from November 17th to 21st, 2024.

BRACIS is the most important event in Brazil for researchers interested in
publishing significant and novel results related to Artificial and
Computational Intelligence. The Brazilian Conference on Intelligent Systems
(BRACIS) originated from the combination of the two most important
scientific events in Brazil in Artificial Intelligence (AI) and
Computational Intelligence (CI): the Brazilian Symposium on Artificial
Intelligence – SBIA (21 editions), and the Brazilian Symposium on Neural
Networks – SBRN (12 editions).  BRACIS, which previously had 12 editions,
will now be recognized as the 34th edition when considering its history and
the 21 editions of SBIA. The 34th BRACIS plays a pivotal role in AI in
Brazil, serving as a hub for promoting theoretical concepts and
applications in Artificial and Computational Intelligence. The event
fosters a space for exchanging scientific ideas among researchers,
practitioners, scientists, and engineers working toward advancing
Artificial and Computational Intelligence science. This aligns with the
goals of other major international conferences proposed in a similar period
in the history of AI, such as the 37th AAAI, 32nd IJCAI, and 37th NeurIPS
(formerly called NIPS). The 33 previous editions of BRACIS highlight the
pioneering of the Brazilian AI Community.

*Please note that this year, we are inaugurating the track submissions.
See further details in the Submission Details section. *

IMPORTANT DATESa

– Paper submission – June 13th, 2024 – AoE*

– Notification to authors – August 10th, 2024.

– Camera-ready copy due – August 20th, 2024.

SPECIAL ISSUES

Authors of the best papers will be invited to submit extended versions of
their work to be appreciated for publication in special issues after the
conference.

SUBMISSION DETAILS

Please note that the BRACIS submission is double-anonymous.  This means
that both the reviewer and author's identities and institutions are
concealed from the reviewers, and vice versa, throughout the review
process. To facilitate this, authors need to ensure that their manuscripts
are prepared in a way that does not reveal their identity.

If you have published a non-anonymous version of your paper online before
paper submission (e.g. arXiv), you can send an anonymous version to the
conference. No references to the non-anonymous version should appear in the
anonymous version, and you should inform the PC chairs that there is a
non-anonymous version. You cannot update the online version nor publish
information regarding the work on social media during the paper review
period, as it can compromise the double-double-anonymous review process.

We strongly encourage making code and data available anonymously (e.g., in
an anonymous GitHub repository via Anonymous GitHub or in a Dropbox folder).

Submitted papers must be written in English and be at most 15 pages,
including all tables, figures, references, and appendices. Formatting
instructions, as well as templates for Word and LaTeX, are available
at ConferenceProceedings guidelines.
Springer's proceedings LaTeX templates are also available in Overleaf.

All submitted papers will be reviewed by at least three experts in the
field. Accepted papers will be included in the BRACIS proceedings and
submitted for publication in Springer in Lecture Notes in Artificial
Intelligence (LNAI) series. Only PDF files can be uploaded to the
submission system.

For each accepted paper, at least one author must register for the
conference and present the paper at the conference venue.

Submissions must be made online using JEMS.

** ATTENTION – About the use of LLMs **

Generative AI models (including Chat-GPT, BARD, LLaMA, Gemini, etc.) or
similar LLMs do not meet the article authorship criteria for BRACIS 2024.
However, we encourage articles that describe research on or involving such
advanced AI models and tools.

Authors who use an LLM in any part of the article writing process take full
responsibility for all content, including checking for plagiarism and
correcting all text. We suggest that this use be properly mentioned in the
Acknowledgments section, with no harm in the evaluation process.

***** Tracks submission: New in this edition ****

This year, BRACIS will have four tracks:

   1. Main track: original works showing novel AI methods with sound results.
   2. AI applications for Social Good: original works presenting novel Social
   Good applications using established AI methods.
   3. General applications: original works presenting novel applications using
   established AI methods, naturally considering the ethical aspects of the
   application.
   4. Published papers: papers published in top AI conferences or journals in
   2023 or 2024 (as a guide, consider the international rankings CS Metrics and CS rankings by selecting AI area or subareas; others can also be considered).

Tracks 1-3 will have no distinction regarding the publication format and
the publication in the proceedings.  For Track 4, authors must submit a
publishable 1-page extended abstract (without references) that does not
violate the copyright of the previous publication.  The accepted papers of
all tracks will have the same slot for presentation during the conference.

TOPICS OF INTEREST

Submissions should include significant and unpublished research on all
aspects of Artificial Intelligence (AI) or Computational Intelligence (CI).
Topics of interest include (but are not restricted to):

– Agent-based and Multi-Agent Systems

– Cognitive Modeling and Human Interaction

– Constraints and Search

– Foundations of AI

– Distributed AI

– Information Retrieval, Integration, and Extraction

– Knowledge Representation and Reasoning

–  Commonsense Reasoning

– Model-Based Reasoning

– Probabilistic Reasoning, and Approximate Reasoning

– Ontologies and the Semantic Web

– Logic-based Knowledge Representation and Reasoning

– Natural Language Processing

– Planning and Scheduling

– Evolutionary Computation and Metaheuristics

– Fuzzy Systems

– Neural Networks

– Deep Learning

– Machine Learning and Data Mining

– Meta-learning

– Reinforcement Learning

– Molecular and Quantum Computing

– Pattern Recognition and Cluster Analysis

– Hybrid Systems

– Bioinformatics and Biomedical Engineering using AI

– Combinatorial and Numerical Optimization

– Computer Vision

– Education for AI and AI for Education

– Forecasting

– Game Playing and Intelligent Interactive Entertainment

– Intelligent Robotics

– Multidisciplinary AI and CI

– Foundation Models

– Large Language Models

– Human-centric AI

– Generative AI

– Ethics in AI

GENERAL CHAIR

André Ponce (ICMC/USP)

PROGRAM CHAIRS

Aline Paes (IC/UFF)

Filipe A. N. Verri (IEC/ITA)