ANTS 2020

COVID-19 Related Information

Sadly, the COVID-19 pandemic has affected the social, economic, and academic life in large parts of the world. Moreover, it seems very hard to forecast the near (even medium) term future. Therefore, we have decided to hold ANTS 2020 as an online conference. The way in which accepted papers are presented will be published in due time on this website.

Call for Papers

Conference Scope

Swarm intelligence is the discipline that deals with the study of self-organizing processes both in nature and in artificial systems. Researchers in ethology and animal behavior have proposed a number of models to explain interesting aspects of collective behaviors such as movement coordination, shape-formation or decision making. Recently, algorithms and methods inspired by these models have been proposed to solve difficult problems in many domains. ANTS 2020 will give researchers in swarm intelligence the opportunity to meet, to present their latest research, and to discuss current developments and applications.

Relevant Research Areas

ANTS 2020 solicits contributions dealing with any aspect of swarm intelligence. Typical, but not exclusive, topics of interest are:
  • Behavioral models of social insects or other animal societies that can stimulate new algorithmic approaches.
  • Empirical and theoretical research in swarm intelligence.
  • Application of swarm intelligence methods, such as ant colony optimization or particle swarm optimization, to real-world problems.
  • Theoretical and experimental research in swarm robotics systems.

Important Dates

  • Extended submission deadline: May 1, 2020
  • Notification of acceptance: July 10, 2020
  • Camera ready copy: July 24, 2020
  • Conference: October 26-28, 2020

As in previous editions, the proceedings will be published in the Springer LNCS Series.

Call for papers in PDF format


Welcome to Barcelona!

For the first time, the ANTS conference would have been held in Barcelona, one of the most interesting and vibrant places in the Mediterranean. The planned conference location was the Residencia d'Investigadors of the Spanish National Research Council (CSIC), in the old center of the city. However, due to the COVID-19 pandemic, we have decided to hold ANTS 2020 as an online conference.


Residencia d'Investigadors
Carrer de l'Hospital, 64
08001 Barcelona
Catalonia, Spain


ANTS 2020
(Attn: Dr. Christian Blum)
Artificial Intelligence Research Institute (IIIA-CSIC)
Campus of the UAB
08193 Bellaterra
Catalonia, Spain
Tel +34-93-5809570
Fax +34-93-5809661
ANTS 2020
(Attn: Dr. Maria J. Blesa)
Universitat Politècnica de Catalunya (UPC)
Omega Building, Office 213
Campus Nord, Carrer de Jordi Girona 1-3
08034 Barcelona
Catalonia, Spain

Accommodation Options

As the conference location is in the heart of Barcelona, you will find many options for accommodation in all price ranges.
It is even possible to reserve accommodation at the conference location. The Residencia d'Investigadors offers rooms at affordable prices: check it out!

Make the best of your lunch breaks!

The conference is located in the Raval neighbourhood, which offers a very large selection of restaurants and street food. For sure you will find a convenient place to satisfy your appetite! Look at the map and choose your favourite place. We will distribute a list of recommended places at the conference!

Conference Information

To be announced

Registration Fee

Authors of accepted paper will be required to pay a registration fee for each accepted paper that will appear in the conference proceedings. The ANTS2020 registration fee is 160 Euros.

The conference fee includes:

  • Admission to all technical online sessions
  • One copy of the conference proceedings

Registration Procedure

Please make your registration here. You will be able to pay by credit card or by bank transfer.

Speaker: Radhika Nagpal

Title: Collective Intelligence, from Nature to Robots

Abstract: In nature, groups of thousands of individuals cooperate to create complex structure purely through local interactions -- from cells that form complex organisms, to social insects like termites that build meter-high mounds and army ants that self-assemble into bridges and nests, to the complex and mesmerizing motion of fish schools and bird flocks. What makes these systems so fascinating to scientists and engineers alike, is that even though each individual has limited ability, as a collective they achieve tremendous complexity.
What would it take to create our own artificial collectives of the scale and complexity that nature achieves? In this talk I will discuss four different ongoing projects that use inspiration from biological self-assembly to create robotic systems: The Kilobot Swarm, inspired by cells, the Termes robots, inspired by mound-building termites, the Eciton soft robots inspired by army ants, and the BlueSwarm project inspired by fish schools. There are many challenges for both building and programming robot swarms, and we use these systems to explore decentralized algorithms, embodied intelligence, and methods forsynthesizing complex global behavior. Our theme is the same: can we create simple robots that cooperate to achieve collective complexity?

Biography: Radhika Nagpal is the Kavli Professor of Computer Science at Harvard University and a member of the Wyss Institute for Biologically Inspired Engineering. At Harvard, she leads the Self-organizing Systems Research Group (SSR) and her research interests span computer science, robotics, and biology. Recent work includes the Termes robots for collective construction and the Kilobot thousand-robot swarm (Science 2014). Her awards include the Microsoft New Faculty Fellowship (2005), NSF Career Award (2007), Borg Early Career Award (2010), Radcliffe Fellowship (2012), the McDonald Mentoring Award (2015), and an invited TED speaker (2017). Nagpal was named by the journal Nature as one of the top ten influential scientists and engineers of the year (Nature 10 award, Dec 2014). Nagpal is also the co-founder of Root Robotics, an educational robotics company aimed at democratizing AI and robotics through early education; her lab's Kilobots have also been commercialized with over 8000 robots sold worldwide.

Speaker: Orit Peleg

Title: Collective Ecophysiology and Physics of Social Insects

Abstract: Collective behavior of organisms creates environmental micro-niches that buffer them from environmental fluctuations e.g., temperature, humidity, mechanical perturbations, etc., thus coupling organismal physiology, environmental physics, and population ecology. This talk will focus on a combination of biological experiments, theory, and computation to understand how a collective of bees can integrate physical and behavioral cues to attain a non-equilibrium steady state that allows them to resist and respond to environmental fluctuations of forces and flows. We analyze how bee clusters change their shape and connectivity and gain stability by spread-eagling themselves in response to mechanical perturbations. Similarly, we study how bees in a colony respond to environmental thermal perturbations by deploying a fanning strategy at the entrance that they use to create a forced ventilation stream that allows the bees to collectively maintain a constant hive temperature. When combined with quantitative analysis and computations in both systems, we integrate the sensing of the environmental cues (acceleration, temperature, flow) and convert them to behavioral outputs that allow the swarms to achieve a dynamic homeostasis.

Biography: Orit Peleg is a broadly trained physicist with a passion for living systems. Her research is aimed at understanding how organisms buffer themselves against large environmental fluctuations and accommodate adaptation over a wide range of length and time scales. This includes protein assemblies that remain intact under varying external mechanical and chemical stimuli, beetles that navigate using volatile celestial cues, and honeybee clusters that change their morphology to both withstand mechanical stresses, and to regulate their bulk temperature. Peleg is an Assistant Professor at the Computer Science Department and the BioFrontiers Institute at the University of Colorado Boulder. She draws from a multidisciplinary background; She holds a B.S. in physics and computer science and an M.S. in physics from Bar-Ilan University in Israel. She then moved to Switzerland to get her Ph.D. in materials science at ETH Zurich, and then to Boston for a Postdoctoral fellowship at Harvard University in first chemistry, and then applied mathematics.

Speaker: Gabriela Ochoa

Title: Complex Networks in Search and Optimisation

Abstract: This talk will present our recent findings and visual (static, animated, 2D, and 3D) maps characterising computational search spaces. Many natural and technological systems are composed of a large number of highly interconnected units; examples are neural networks, biological systems, social interacting species, the Internet, and the World Wide Web. A key approach to capture the global properties of such systems is to model them as graphs whose nodes represent the units, and whose links stand for the interactions between them. This simple, yet powerful concept has been used to study a variety of complex systems where the goal is to analyse the pattern of connections between components in order to understand the behaviour of the system.
This talk overviews recent results on local optima networks (LONs), a network-based model of fitness landscapes where nodes are local optima and edges are possible search transitions among these optima. We will also introduce search trajectory networks (STNs) as a tool to analyse and visualise the behaviour of metaheuristics. STNs model the search trajectories of algorithms. Unlike LONs, nodes are not restricted to local optima but instead represent given states of the search process. Edges represent search progression between consecutive states. This extends the power and applicability of network-based models. Both LONs and STNs allow us to visualise realistic search spaces in ways not previously possible and bring a whole new set of quantitative network metrics for characterising and understanding computational search.

Biography: Gabriela Ochoa is a Professor of Computing Science at the University of Stirling in Scotland. Her research lies in the foundations and applications of evolutionary algorithms and metaheuristics, with emphasis on autonomous search, fitness landscape analysis and visualisation, combinatorial optimisation and applications to healthcare. She holds a PhD from the University of Sussex, UK, and has held academic and research positions at the University Simon Bolivar, Venezuela, and the University of Nottingham, UK. Her recent work on network-based models of fitness landscapes has enhanced their descriptive and visualisation capabilities, producing a number of publications including 4 best-paper awards and 3 other nominations at leading venues. She has been active in organisation and editorial roles within leading Evolutionary Computation venues such as the Genetic and Evolutionary Computation Conference (GECCO), Parallel Problem Solving from Nature (PPSN), and the Evolutionary Computation Journal (ECJ).


Organizing Committee

General chairs
Marco Dorigo and Thomas Stützle, Université Libre de Bruxelles, Brussels
Local organisation and publicity chairs
Maria J. Blesa, Universitat Politècnica de Catalunya (UPC), Barcelona
Christian Blum, Artificial Intelligence Research Institute (IIIA-CSIC), Barcelona
Technical program chairs
Christian Blum, Artificial Intelligence Research Institute (IIIA-CSIC), Barcelona
Heiko Hamann, University of Lübeck, Lübeck
Publication chair
Mary Katherine Heinrich, Université Libre de Bruxelles, Brussels
Paper submission chair
Volker Strobel, Université Libre de Bruxelles, Brussels

Program Committee (to be updated)

  • Ashraf Abdelbar, Brandon University
  • Michael Allwright, Université Libre de Bruxelles
  • Martyn Amos, Northumbria University
  • Jacob Beal, BBN Technologies
  • Giovanni Beltrame, Ecole Polytechnique de Montreal
  • Spring Berman, Arizona State University
  • Tim Blackwell, Goldsmiths, University of London
  • Wei-Neng Chen, Sun Yat-Sen University
  • Guido de Croon, Delft University of Technology
  • Gianni Di Caro, Carnegie Mellon University
  • Luca Di Gaspero, University of Udine
  • Eliseo Ferrante, University of Birmingham
  • Ryusuke Fujisawa, Hachinohe Institute of Technology
  • Luca Maria Gambardella, Istituto Dalle Molle di Studi sull'Intelligenza Artificiale
  • José García-Nieto, University of Málaga
  • Simon Garnier, New Jersey Institute of Technology
  • Morten Goodwin, University of Agder
  • Roderich Gross, The University of Sheffield
  • Yara Khaluf, Ghent University
  • Xiaodong Li, RMIT University
  • Simone Ludwig, North Dakota State University
  • Manuel López-Ibáñez, The University of Manchester
  • Vittorio Maniezzo, University of Bologna
  • Massimo Mastrangeli, Delft University of Technology
  • Clerc Maurice, Independent Consultant on Optimisation
  • Bernd Meyer, Monash University
  • Martin Middendorf, University of Leipzig
  • Marco Montes de Oca, Northeastern University
  • Melanie Moses, University of New Mexico
  • Kazuhiro Ohkura, Hiroshima University
  • Konstantinos Parsopoulos, University of Ioannina
  • Orit Peleg, University of Colorado Boulder
  • Paola Pellegrini, IFSTTAR
  • Carlo Pinciroli, Worcester Polytechnic Institute
  • Günther Raidl, Vienna University of Technology
  • Mike Rubenstein, Northwestern University
  • Roberto Santana, University of the Basque Country
  • Thomas Schmickl, University of Graz
  • Kevin Seppi, Brigham Young University
  • Dirk Sudholt, The University of Sheffield
  • Munehiro Takimoto, Tokyo University of Science
  • Danesh Tarapore, University of Southampton
  • Guy Theraulaz, CNRS - Université Paul Sabatier
  • Dhananjay Thiruvady, Deakin University
  • Elio Tuci, University of Namur
  • Ali Emre Turgut, Middle East Technical University
  • Gabriele Valentini, Arizona State University
  • Justin Werfel, Harvard University
  • Masahito Yamamoto, Hokkaido University
  • Cheng-Hong Yang, National Kaohsiung University of Applied Sciences
  • Zhi-Hui Zhan, South China University of Technology


Relevant information will be provided in due course

Submission link: Submit a paper!

Deadline: May 1, 2020

Initial submission instructions

Submissions may be a maximum of 11 pages, excluding references, when typeset in the LNCS Springer LaTeX template. Submissions should be a minimum of 7 full pages.

This strict page limit includes figures, tables, and all supplementary sections (e.g., Acknowledgements). The only exclusion from the page limit is the reference list, which should be of any length that properly positions the paper with respect to the state of the art.

Papers should be prepared in English, in the LNCS Springer LaTeX style, using the default font and font size. Authors should consult Springer’s authors’ guidelines and use their proceedings template for LaTeX, for the preparation of their papers. Please download the LNCS Springer LaTeX template package (zip, 294 Kb) and authors' guidelines (pdf, 288 Kb) directly from the Springer website. Please also download and consult the ANTS 2020 sample LaTeX document (zip, 203 Kb), which shows the correct options to use within the Springer template.

Submissions that do not respect these guidelines will not be considered.

Note: Authors may find it convenient that Springer’s proceedings LaTeX templates are available in Overleaf

The initial submission must be in PDF format.

Please note that in the camera-ready phase, authors of accepted papers will need to submit both a compiled PDF and all source files (including LaTeX files and figures).

The camera-ready phase will have more detailed formatting requirements than the initial submission phase. Authors are invited to consult these camera-ready instructions preemptively.

Submission process

Submitted papers will be peer-reviewed on the basis of technical quality, relevance, significance, and clarity. If a submission is not accepted as a full length paper, it may still be accepted either as a short paper or as an extended abstract. In such cases, authors will be asked to reduce the length of the submission accordingly. Authors of all accepted papers will be asked to execute revisions, based on the reviewers’ comments.

Camera-ready submission instructions

Accepted papers are to be revised and submitted as a camera-ready version. Reviewers’ comments should be taken into account and should guide appropriate revisions. The camera-ready submission must include the compiled PDF and all source files needed for compilation—including the LaTex file, reference file, and figures.

By submitting a camera-ready paper, the author(s) agree that at least one author will attend the conference and give a presentation of the paper. At least one author must be registered by the deadline for camera-ready submissions.

Camera-ready submissions that do not comply with all given requirements might have to be excluded from the conference proceedings.

After formatting the paper as explained below, please follow the subsequent instructions for submitting a zip/tar file that contains your camera-ready paper sources:

  1. Visit the EasyChair website and log in.
  2. Choose Role: author for the conference ANTS 2020.
  3. Click on the magnifying lens symbol in the column View for your submission(s).
  4. Click on Add or update files at the top right of the page.
  5. Upload either a zip archive or a tgz archive by clicking on Choose file.
  6. Finalize your submission by clicking on Submit.

Deadline for submission: July 24, 2020

Formatting instructions

Papers must be prepared in the LNCS Springer LaTeX style, using the default font and font size. Authors should consult Springer’s authors’ guidelines and use their proceedings template for LaTeX, for the preparation of their papers. Please download the LNCS Springer LaTeX template package (zip, 294 Kb) and authors' guidelines (pdf, 288 Kb) directly from the Springer website. The LaTeX class and references style (llncs.cls and splncs04.bst) included in this package should not be modified. Please also download and consult the ANTS 2020 sample LaTeX document (zip, 203 Kb), which shows the correct options to use within the Springer template.

Your submission should be uploaded as a compressed archive (zip, tgz), containing the final camera-ready versions of the following:

  • the compiled PDF (pdf),
  • the main LaTeX file (tex),
  • the references file (both in bib and bbl),
  • and all figures, where applicable (pdf, eps, png, jpeg, tiff, bmp).

Figures should be in their original vector format (pdf, eps), if applicable. Otherwise, figures provided in raster format (png, jpeg, tiff, bmp) must be high-resolution (if including linework, at least 800 dpi at the final size, otherwise, at least 300 dpi at the final size).

Although figures in the digital proceedings will be in full color, the print proceedings of ANTS 2020 will be printed in grayscale. Authors should therefore ensure that their figures will be appropriately legible when printed in grayscale.

Springer encourages authors to include their ORCIDs in their papers. In addition, the corresponding author of each paper, acting on behalf of all of the authors of that paper, must complete and sign a Consent-to-Publish form. The corresponding author signing the copyright form should match the corresponding author marked on the paper. Once the files have been sent to Springer, changes relating to the authorship of the papers cannot be made.

Information regarding the copyright form. The proceedings title will be Swarm Intelligence, 12th International Conference, ANTS 2020. The editors of the proceedings will be Marco Dorigo, Maria J. Blesa, Christian Blum, Heiko Hamann, Mary Katherine Heinrich, Volker Strobel.

Number of pages

Full-length Papers are strictly limited to 11 pages + references, and Short Papers are strictly limited to 7 pages + references.

These page limits include figures, tables, and all supplementary sections (e.g., Acknowledgements). The only exclusion from these page limits is the reference list, which should have an appropriate length with respect to the state of the art.

Extended Abstracts are strictly limited to 2 pages (including references).

All page limits refer to papers prepared in the LNCS Springer LaTeX template, according to the instructions provided here. Do not modify the template defaults, such as those for margins, line spacing, or font size.

Using the LNCS Springer LaTeX style

Submissions must be prepared in LaTeX, and the source files (tex, bib, bbl) must be provided. Authors should use the LaTeX class and references style files (llncs.cls and splncs04.bst) as provided in the LNCS Springer LaTeX template package. These files should not be modified. Also, do not add formatting modifications to the main document (tex) to override the template defaults. Do not use, for instance, any line spacing modifications (e.g., \vspace{} or \\*[0pt]), or font size modifications (e.g., \fontsize{}). Please do not add any special fonts. Please do not add packages or custom commands that change the formatting (e.g., do not use the package subcaption, as it overrides the default caption formatting in the template).

During the final preparation of the proceedings, any formatting modifications in the main document (tex) will be removed if they do not match the template, potentially causing a change in paper length. Springer will also recompile all papers using their original llncs class file (llncs.cls). If authors make any modifications to the llncs file, their paper will not compile correctly in the final step, and cannot be included in the proceedings.

References must be formatted using the provided references style file (splncs04.bst). In this references style, in-text citations will appear as numbers, and the numbered reference list will be ordered alphabetically.

For further information, please refer to the class documentation included in the LNCS Springer LaTex package, and to the LNCS Springer authors’ guidelines.

ANTS 2020 formatting details

It is mandatory that submissions to ANTS 2020 follow certain options within the LNCS Springer template. The ANTS 2020 sample LaTeX document (zip, 203 Kb) shows the correct template options to use. These mandatory template options are as follows.

Running header:

  • The running header option should be activated. This is activated by starting your LaTeX document (tex) with the command: \documentclass[runningheads]{llncs}.
  • In the author-running field: \authorrunning{}, give the initial of the first name(s) and the full surname. Always give the first author's name. If there are precisely two authors, then give both the first and second authors' names. If there are more than two authors, use ‘et al.’ after the name of the first author.
  • If the title is too long for the header, specify a shorter header title using the title-running field: \titlerunning{Abbreviated paper title}.

Title and headings:

  • The title, headings, and subheadings should be capitalized according to standard ‘Title Case’ style (i.e., all words should be capitalized, except for articles, prepositions, and conjunctions).
  • Do not use a \newline command with the title.
  • Headings and subheadings should be aligned to the left.

Author names and affiliations:

  • Follow the naming convention in which the surname is the last name.
  • Using the LaTex \author{} field, provide the full first name (not only the initial).
  • Do not include academic titles (e.g., Prof. or Dr.).
  • Springer encourages the inclusion of author ORCIDs. These can be optionally included using the LaTex field \orcidID{} within the LaTex field \author{}.
  • Author affiliation information should include the following, using the \institute{} and \email{} fields: department, faculty, university, company (if applicable), city, country, and email address. Do not include the street address or ZIP code (it is not a postal address). The email address of the corresponding author is mandatory to include in the \institute{} and \email{} fields.
  • After the \institute{} entries, include an \index{} entry for each author, giving the full surname, followed by the full first name(s).

For further details, please refer to the documentation of the llncs class.


  • Acknowledgements, if any, should be given as the last subsubsection of the paper, just before the list of references.
  • Do not format acknowledgments as a footnote, anywhere in the paper.


  • Do not include keywords in your manuscript; they will not be included in the proceedings.

For contributions accepted as Extended Abstracts:

  • Extended Abstract submissions must not contain an abstract, and must not include any section headings (or subheadings) in the main body. (Other than the title, the only headings in the manuscript should be for the References and Acknowledgments, if applicable).

Proceedings and journal special issue

Conference proceedings will be published by Springer in the LNCS series.

The journal Swarm Intelligence will publish a special issue dedicated to ANTS 2020, containing extended versions of the best papers presented at the conference.

Last modification: July 10, 2020.