Gabriele Valentini

Associate Research Scientist
School of Life Sciences
Arizona State University

Information flow during tandem runs

Signals whose function is solely to coordinate communication are so far known only in human conversations and telecommunication networks. Utterances like “mm-hmm”, gestures such as the nodding of one’s head, or “ACK” packets used in Internet protocols to confirm the reception of a message all coordinate communication. Quantitative comparison of information flows between sender-receiver pairs demonstrates that acknowledgements are used by pairs of ants during tandem running—a social behaviour where the sender facilitates the receiver’s intake of navigational information—but not by pairs of termites that also tandem run to maintain cohesion but not to share large amounts of information.

More information about this project can be found in: P4 and W13.

Information flow in slime molds

Despite lacking a brain, the slime mold Physarum polycephalum can solve complex optimization problems such as navigating a maze and solving a tower of Hanoi. Understanding how P. polycephalum can do so has the potential to unravel the function of more complex collective animal behaviors as well as to facilitate the design of distributed artificial systems. The gathering, transfer and processing of information is central to the problem-solving ability of P. polycephalum and formal information-theoretic approaches can provide novel perspectives and research directions. In this study, we investigated the transfer of information along a single tubule of P. polycephalum tasked with a binary decision-making problem between two food sources. Using the construct of transfer entropy, we analyzed the direction and magnitude of information transfer and found that these differ as a function of the relative quality of the food sources. Unexpectedly, when a difference in food quality exists, information is transferred from the region of the slime mold in contact with the lower quality food towards that in contact with the higher quality food pointing future research efforts to investigate more closely the mechanisms in place in this region.

More information about this project can be found in: J10.

DOL, spread of information & colony emigrations

The fitness of group-living animals often depends on the efficiency with which members share information about resources, so that the group can collectively decide how best to allocate its efforts. Theoretical studies have shown that collective choices can emerge from homogeneous individuals following identical rules, but real animals show much evidence for heterogeneity in the degree and nature of their contribution to group decisions. In social insects, for example, the transmission and processing of information is influenced by an often-neglected but well-organized division of labor of behaviorally heterogeneous workers. In this study, we look at nest choices during colony emigrations of the ant Temnothorax rugatulus and measure the degree of behavioral heterogeneity of workers. Using both machine learning and network analysis methods, we identify and characterize four behavioral categories of workers — primary, secondary, passive, and wandering — and analyze workers’ contributions to the spread of information during each emigration.

Read more about this project: J12.

Collective decisions in robot swarms

This project focuses on the design and mathematical analysis of collective decision-making strategies for swarms of autonomous robots. In a robot swarm, the cognitive abilities of individual robots may prove too limited with respect to the complexity of the problem at hand; yet, by cooperating with each other, the robots in a swarm can overcome their cognitive limitations by aggregating information at the collective level obtaining superior collective decisions. In this project, we investigate the development of a modular and model-driven methodology to design collective decision-making strategies for the best-of-n problem, that is, the problem of finding the best among a finite set of options. We put forward a methodology supported by a macroscopic mathematical framework that allows designers to study the dynamics of a swarm across different levels of abstraction: from mean field approximations that allow for the study of the asymptotic properties of a strategies, to stochastic mathematical models that account for finite-size effects in swarms with finite number of robots.

More information about this project can be found in: B1, J2, J4, J5, C4, C6, C7, C9, C10, C11 and C14.

Collective construction of nest architecture

Ant colonies build nest that result from the collective contribution of a large number of individuals. The characteristic features of nest architecture reflect the diversity of colony members and are hardly predicted from individual phenotypes. This project, lead by Christina L. Kwapich, investigates the non-additive effects of polymorphism in the nest architecture of the harvester ant Veromessor pergandei. Experiments were performed by varying the ratio of large and small workers in colonies composed of a fixed number of individuals. We then studied the resulting nest architectures using tools from network analysis showing that mixed-size colonies build longer nests, excavate more sand and produce greater architectural complexity than single-sized worker groups. The nest architectures built by mixed-size colonies was not predicted by the combined contributions of colonies composed of only small or only large workers.

More information about this project can be found in: J8.

The Kilogrid platform

The Kilogrid is an open-hardware virtualization environment and data logging manager for the Kilobot robot. The Kilogrid is designed to extend the sensory-motor abilities of the Kilobot robot, to simplify the task of collecting data during experiments, and to provide researchers with a tool to fine-control the parameters of the experimental setup. Based on the design of the Kilobot robot and compatible with existing hardware, the Kilogrid is a modular system composed of a grid of computing nodes, or modules, that provides a bidirectional communication channel between the Kilobots and a remote workstation. In the videos below you can observe several demo experiments that showcase the implementation of virtual sensors, virtual actuators, and data logging.

More information about the Kilogrid can be found in: J7 and C12.

The rinform package

rinform is a computationally-efficient R package for performing information-theoretic analysis of time series data. rinform is one of a suit of wrappers for the Inform v1.0.0 C library developed by Douglas G. Moore which includes wrappers in Python as well as Mathematica Wolfram language. As for the Inform library, it is structured around the concepts of: 1) discrete empirical probability distributions, which form the basis for all of its information-theoretic measures, 2) classic information-theoretic measures built upon empirical distributions, and 3) measures of information dynamics for time series. In addition to its core components, rinform also provides a collection of utilities to manipulate time series.

More information about rinform can be found in: J9 and C13.

Publications

Preprints

  1. G. Valentini, H. Hamann, M. Dorigo. Global-to-Local Design for Self-Organized Task Allocation in Swarms. IRIDIA Technical Report Series, TR/IRIDIA2016-002r001, 2016

Books

  1. G. Valentini Achieving Consensus in Robot Swarms. Design and Analysis of Strategies for the best-of-n Problem. Studies in Computational Intelligence, Volume 706, Springer, 2017
    @book{Valentini2017, 
      author    = {Gabriele Valentini}, 
      title     = {Achieving Consensus in Robot Swarms: {D}esign and Analysis of Strategies for the best-of-$n$ Problem}, 
      year      = {2017}, 
      publisher = {Springer International Publishing}, 
      address   = {Cham, Switzerland},
      volume    = {706},
      series    = {Studies in Computational Intelligence},
      pages     = {9--32}, 
      isbn      = {978-3-319-53609-5} 
    }

Journals

Articles where I'm (one of) the corresponding author(s).
  1. N. Mathews, G. Valentini, A. L. Christensen, R. O'Grady, A. Brutschy, M. Dorigo. Spatially Targeted Communication in Decentralized Multirobot Systems. Autonomous Robots, 38(4):439–457, 2015 IF 2015: 1.547
    @article{MatValChrOGrBruDor2015,
      year      = {2015},
      issn      = {0929-5593},
      journal   = {Autonomous Robots},
      doi       = {10.1007/s10514-015-9423-6},
      title     = {Spatially targeted communication in decentralized multirobot systems},
      url       = {http://dx.doi.org/10.1007/s10514-015-9423-6},
      publisher = {Springer},
      keywords  = {Decentralized multirobot systems; Robot swarms; 
                   Air-ground robot teams; Spatial coordination; 
                   Inter-robot communication},
      author    = {Mathews, Nithin and Valentini, Gabriele and Christensen, Anders Lyhne 
                   and O’Grady, Rehan and Brutschy, Arne and Dorigo, Marco},
      volume    = {38},
      number    = {4},
      pages     = {439--457}
    }
  2. G. Valentini, H. Hamann. Time-Variant Feedback Processes in Collective Decision-Making Systems: Influence and Effect of Dynamic Neighborhood Sizes. Swarm Intelligence, 8(2–3):153–176, 2015 IF 2015: 2.577
    @article{ValHam2015,
      year      = {2015},
      issn      = {1935-3812},
      journal   = {Swarm Intelligence},
      doi       = {10.1007/s11721-015-0108-8},
      title     = {Time-variant feedback processes in collective decision-making systems: 
                   influence and effect of dynamic neighborhood sizes},
      url       = {http://dx.doi.org/10.1007/s11721-015-0108-8},
      publisher = {Springer},
      keywords  = {Swarm system; Feedbacks; Opinion dynamics; Renormalization group; Graph theory},
      author    = {Valentini, Gabriele and Hamann, Heiko},
      volume    = {8},
      number    = {2--3},
      pages     = {153--176}
    }
  3. A. Reina, G. Valentini, C. Fernández-Oto, M. Dorigo, V. Trianni. A Design Pattern for Decentralized Decision Making. PLoS ONE, 10(10):e0140950, 2015 IF 2015: 3.057
    @article{ReiValFerDorTri2015,
      author    = {Reina, Andreagiovanni AND Valentini, Gabriele AND Fern\'andez-Oto, Cristian AND Dorigo, Marco AND Trianni, Vito},
      journal   = {PLoS ONE},
      publisher = {Public Library of Science},
      title     = {A Design Pattern for Decentralised Decision Making},
      year      = {2015},
      month     = {10},
      volume    = {10},
      url       = {http://dx.doi.org/10.1371%2Fjournal.pone.0140950},
      pages     = {e0140950},
      number    = {10},
      doi       = {10.1371/journal.pone.0140950}
    }
  4. G. Valentini, E. Ferrante, H. Hamann, M. Dorigo. Collective Decision with 100 Kilobots: Speed Versus Accuracy in Binary Discrimination Problems. Autonomous Agents and Multi-Agent Systems, 30(3):553–580, 2016 IF 2016: 1.606
    @article{ValFerHamDor2016,
      author     = {Gabriele Valentini and Eliseo Ferrante and Heiko Hamann and Marco Dorigo},
      title      = {Collective decision with 100 {K}ilobots: {S}peed versus accuracy in binary discrimination problems},
      year       = {2016},
      journal    = {Autonomous Agents and Multi-Agent Systems},
      publisher  = {Springer},
      volume     = {30},
      number     = {3},
      issn       = {1573-7454},
      doi        = {10.1007/s10458-015-9323-3},
      url        = {http://dx.doi.org/10.1007/s10458-015-9323-3},
      pages      = {553--580}
    }
  5. G. Valentini, E. Ferrante, M. Dorigo. The Best-of-n Problem in Robot Swarms: Formalization, State of the Art, and Novel Perspectives. Frontiers in Robotics and AI, 4:9, 2017
    @article{ValFerDor2017,
      author     = {Gabriele Valentini and Eliseo Ferrante and Marco Dorigo},
      title      = {The Best-of-\emph{n} Problem in Robot Swarms: {F}ormalization, 
                    State of the Art, and Novel Perspectives},
      year       = {2017},
      journal    = {Frontiers in Robotics and AI},
      volume     = {4},
      issn       = {2296-9144},
      doi        = {10.3389/frobt.2017.00009},
      url        = {http://journal.frontiersin.org/article/10.3389/frobt.2017.00009},
      pages      = {9}
    }
  6. Y. Khaluf, C. Pinciroli, G. Valentini, H. Hamann. The Impact of Agent Density on Scalability in Collective Systems: Noise-Induced vs Majority-Based Bistability. Swarm Intelligence, 1(2):155–179, 2017 IF 2017: 1.520
    @article{KhaPinValHam2017,
      author     = {Yara Khaluf and Carlo Pinciroli and Gabriele Valentini and Heiko Hamann},
      title      = {The Impact of Agent Density on Scalability in Collective Systems: 
                    Noise-Induced vs Majority-Based Bistability},
      year       = {2017},
      journal    = {Swarm Intelligence},
      volume     = {11},
      number     = {2},
      issn       = {1935-3820},
      doi        = {10.1007/s11721-017-0137-6},
      url        = {http://dx.doi.org/10.1007/s11721-017-0137-6},
      pages      = {155--179}
    }
  7. G. Valentini, A. Antoun, M. Trabattoni, B. Wiandt, Y. Tamura, E. Hacquard, V. Trianni, M. Dorigo. Kilogrid: A Novel Experimental Environment for the Kilobot Robot. Swarm Intelligence, 12(3):245–266, 2018 IF 2018: 2.208
    @article{ValAntTraTamHacTriDor2018,
      author     = {Gabriele Valentini and Athony Antoun and Marco Trabattoni and 
                    Bern\'at Wiandt and Yasumasa Tamura and Etienne Hacquard and Vito Trianni and Marco Dorigo},
      title      = {Kilogrid: A Novel Experimental Environment for the Kilobot Robot},
      year       = {2018},
      journal    = {Swarm Intelligence},
      volume     = {12},
      number     = {3},
      issn       = {1935-3812},
      doi        = {10.1007/s11721-018-0155-z},
      url        = {https://link.springer.com/article/10.1007/s11721-018-0155-z},
      pages      = {245--266}
    }
  8. C.L. Kwapich, G. Valentini, B. Hölldobler. The Non-Additive Effects of Body Size on Nest Architecture in a Polymorphic Ant. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1753), 2018 IF 2018: 6.139
    @article{KwaValHol2018,
      author     = {Christina L. Kwapich and Gabriele Valentini and Bert H\"olldobler},
      title      = {The Non-Additive Effects of Body Size on Nest Architecture in a Polymorphic Ant.},
      year       = {2018},
      journal    = {Philosophical Transactions of the Royal Society B: Biological Sciences},
      volume     = {373},
      number     = {1753},
      pages      = {20170235},
      doi        = {10.1098/rstb.2017.0235}  
      url        = {https://royalsocietypublishing.org/doi/abs/10.1098/rstb.2017.0235},
      issn       = {0962-8436}
    }
  9. D.G. Moore, G. Valentini, S.I. Walker, M. Levin. Inform: Efficient Information-Theoretic Analysis of Collective Behaviors. Frontiers in Robotics and AI, 5:60, 2018
    @article{MooValWalLev2018,
      author     = {Douglas G. Moore and Gabriele Valentini and Sara Imari Walker and Michael Levin},
      title      = {Inform: {E}fficient Information-Theoretic Analysis of Collective Behaviors},
      year       = {2018},
      journal    = {Frontiers in Robotics and AI},
      volume     = {5},
      issn       = {2296-9144},
      doi        = {10.3389/frobt.2018.00060},
      pages      = {60}
      }
  10. S.K. Ray, G. Valentini, P. Shah, A. Haque, C.R. Reid, G.F. Weber, S. Garnier. Information Transfer During Food Choice in the Slime Mold Physarum polycephalum. Frontiers in Ecology and Evolution, 7:67, 2019 IF 2019: 2.416
    @article{RayValPurHaqReiWebGar2019,
      author     = {Ray, Subash K. and Valentini, Gabriele and Shah, Purva and Haque, Abid and Reid, Chris R. and Weber, Gregory F. and Garnier, Simon},
      title      = {Information Transfer During Food Choice in the Slime Mold \textit{Physarum polycephalum}},
      year       = {2019},
      journal    = {Frontiers in Ecology and Evolution},
      volume     = {7},
      issn       = {2296-701X},
      doi        = {10.3389/fevo.2019.00067},
      pages      = {67}
      }
  11. G. Valentini. How Robots in a Large Group Make Decisions as a Whole? From Biological Inspiration to the Design of Distributed Algorithms. Journal of The Society of Instrument and Control Engineers (計測と制御), 59(2):90–98, 2020
    @article{Val2020,
      author     = {Valentini, Gabriele},
      title      = {How Robots in a Large Group Make Decisions as a Whole? From Biological Inspiration to the Design of Distributed Algorithms},
      year       = {2020},
      journal    = {Journal of The Society of Instrument and Control Engineers},
      volume     = {59},
      issue      = {2},
      doi        = {10.11499/sicejl.59.90},
      pages      = {90--98}
    }
  12. G. Valentini, N. Masuda, Z. Shaffer, J.R. Hanson, T. Sasaki, S.I. Walker, T.P. Pavlic, S.C. Pratt. Division of labor promotes the spread of information in colony emigrations by the ant Temnothorax rugatulus. Proceedings of the Royal Society B: Biological Sciences, 287(1924):20192950 2020 IF 2019: 4.637
    @article{ValMasShaHanSasWalPavPra2020,
      author     = {Valentini, Gabriele and Masuda, Naoki and Shaffer, Zachary and Hanson,  Jake R. and Sasaki, Takao and Walker, Sara Imari and Pavlic,  Theodore P. and Pratt,  Stephen C.},
      title      = {Division of labor promotes the spread of information in colony emigrations by the ant \textit{Temnothorax rugatulus}},
      year       = {2020},
      journal    = {Proceedings of the Royal Society B: Biological Sciences},
      volume     = {287},
      issue      = {1924},
      doi        = {10.1098/rspb.2019.2950},
      pages      = {20192950}
    }
  13. G. Valentini, N. Mizumoto, S.C. Pratt, T.P. Pavlic, S.I. Walker. Revealing the structure of information flows discriminates similar animal social behaviors. eLife (accepted) 2020 IF 2019: 7.08
    @article{ValMizPraPavWal2020,
      author     = {},
      title      = {},
      year       = {2020},
      journal    = {},
      volume     = {},
      issue      = {},
      doi        = {},
      pages      = {}
    }

Conferences

  1. G. Valentini, L. Malagò, M. Matteucci. Evoptool: an Extensible Toolkit for Evolutionary Optimization Algorithms Comparison. In Proceedings of the IEEE World Congress on Computational Intelligence, Congress on Evolutionary Computation WCCI-CEC 2010, pag. 2475–1482, IEEE Press, 2010
    @inproceedings{ValMalMat2010,
      title        = {{Evoptool: an extensible toolkit for evolutionary optimization algorithms comparison}},
      author       = {Valentini, G. and Malag\`{o}, L. and Matteucci, M.},
      booktitle    = {Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2010},
      pages        = {2475--2482},
      year         = {2010},
      publisher    = {IEEE Press}
      }
  2. L. Malagò, M. Matteucci, G. Valentini. Introducing ℓ1-regularized Logistic Regression in Markov Networks based EDAs. In Proceedings of the IEEE Congress on Evolutionary Computation CEC 2011, pag. 1581–1588, IEEE Press, 2011
    @inproceedings{MalValMat2011,
      title        = {{Introducing $\ell_{1}$-regularized logistic regression in Markov Networks based EDAs}},
      author       = {Malag\`{o}, L. and Matteucci, M. and Valentini, G.},
      booktitle    = {Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2011},
      pages        = {1581--1588},
      year         = {2011},
      publisher    = {IEEE Press}
      }
  3. G. Valentini, L. Malagò, M. Matteucci. Optimization by ℓ1-Constrained Markov Fitness Modelling. Learning and Intelligent Optimization LION6, vol. 7219 of LNCS, pag. 250–264, Springer, 2012
    @inproceedings{ValMalMat2012,
      title        = {{Optimization by $\ell_{1}$-Constrained a Markov Fitness Modelling}},
      author       = {Valentini, Gabriele and Malag\`{o}, Luigi and Matteucci, Matteo},
      booktitle    = {Learning and Intelligent Optimization},
      series       = {Lecture Notes in Computer Science},
      editor       = {Hamadi, Youssef and Schoenauer, Marc},
      publisher    = {Springer},
      isbn         = {978-3-642-34412-1},
      pages        = {250-264},
      volume       = {7219},
      doi          = {http://dx.doi.org/10.1007/978-3-642-34413-8_18},
      year         = {2012}
      }
  4. G. Valentini, M. Birattari, M. Dorigo. Majority Rule with Differential Latency: An Absorbing Markov Chain to Model Consensus. Proceedings of the European Conference on Complex Systems ECCS 2012, Springer Proceedings in Complexity, pag. 651–658, Springer, 2013
    @inproceedings{ValBirDor2013,
      year        = {2013},
      isbn        = {978-3-319-00394-8},
      booktitle   = {Proceedings of the European Conference on Complex Systems 2012},
      series      = {Springer Proceedings in Complexity},
      editor      = {Gilbert, Thomas and Kirkilionis, Markus and Nicolis, Gregoire},
      doi         = {10.1007/978-3-319-00395-5_79},
      title       = {Majority Rule with Differential Latency: An Absorbing {M}arkov Chain to Model Consensus},
      publisher   = {Springer},
      author      = {Valentini, Gabriele and Birattari, Mauro and Dorigo, Marco},
      pages       = {651-658}
      }
  5. H. Hamann, G. Valentini. Swarm in a Fly Bottle: Feedback-Based Analysis of Self-Organizing Temporary Lock-Ins. Swarm Intelligence, Proceedings of the Ninth International Conference on Swarm Intelligence ANTS 2014, vol. 8667 of LNCS, pag. 170–181, Springer, 2014
    @inproceedings{HamVal2014,
      year       = {2014},
      isbn       = {978-3-319-09951-4},
      booktitle  = {Swarm Intelligence},
      volume     = {8667},
      series     = {LNCS},
      editor     = {Dorigo, Marco and Birattari, Mauro and Garnier, Simon and Hamann, Heiko and Montes de Oca, Marco and Solnon, Christine and St\"utzle, Thomas},
      doi        = {10.1007/978-3-319-09952-1_15},
      title      = {Swarm in a Fly Bottle: Feedback-Based Analysis of Self-organizing Temporary Lock-ins},
      publisher  = {Springer},
      author     = {Hamann, Heiko and Valentini, Gabriele},
      pages      = {170-181}
      }
  6. H. Hamann, G. Valentini, Y. Khaluf, M. Dorigo. Derivation of a Micro-Macro Link for Collective Decision-Making Systems: Uncover Network Features Based on Drift Measurements. In Proceedings of the 13th International Conference on Parallel Problem Solving from Nature PPSN XIII, vol. 8672 of LNCS, pag. 181–190, Springer, 2014
    @inproceedings{HamValKalDor2014,
      year       = {2014},
      isbn       = {978-3-319-10761-5},
      booktitle  = {Parallel Problem Solving from Nature -- PPSN XIII},
      volume     = {8672},
      series     = {LNCS},
      editor     = {Bartz-Beielstein, Thomas and Branke, J\"urgen and Filipi\v{c}, Bogdan and Smith, Jim},
      doi        = {10.1007/978-3-319-10762-2_18},
      title      = {Derivation of a Micro-Macro Link for Collective Decision-Making Systems: Uncover Network Features Based on Drift Measurements},
      publisher  = {Springer},
      author     = {Hamann, Heiko and Valentini, Gabriele and Khaluf, Yara and Dorigo, Marco},
      pages      = {181-190}
      }
  7. G. Valentini, H. Hamann, M. Dorigo. Self-Organized Collective Decision Making: The Weighted Voter Model. In Proceedings of 13th International Conference on Autonomous Agents and Multiagent Systems AAMAS 2014, pag. 45–52, IFAAMAS, 2014
    @inproceedings{ValHamDor2014,
      author      = {Gabriele Valentini and Heiko Hamann and Marco Dorigo},
      title       = {Self-Organized Collective Decision Making: The Weighted Voter Model},
      booktitle   = {Proceedings of the 13th Int. Conf. on Autonomous Agents and Multiagent Systems},
      pages       = {45--52},
      year        = {2014},
      editor      = {Alessio Lomuscio and Paul Scerri and Ana Bazzan and Michael Huhns},
      series      = {AAMAS '14},
      publisher   = {IFAAMAS},
      }
  8. G. Valentini, H. Hamann, M. Dorigo. Self-Organized Collective Decision-Making in a 100-Robot Swarm. In Proceedings of the 29th AAAI Conference on Artificial Intelligence AAAI 2015, Student Abstract, pag. 4216–4217, AAAI Press, 2015
    @inproceedings{ValHamDor2015a,
      author      = {Gabriele Valentini and Heiko Hamann and Marco Dorigo},
      title       = {Self-Organized Collective Decision-Making in a 100-Robot Swarm},
      key         = {collective decision making, majority rule, consensus, 
                     swarm intelligence, swarm robotics, self-organization, 
                     modeling},
      pages       = {4216--4217},
      conference  = {AAAI Conference on Artificial Intelligence},
      year        = {2015},
      publisher   = {AAAI Press}
      }
  9. G. Valentini, H. Hamann, M. Dorigo. Efficient Decision-Making in a Self-Organizing Robot Swarm: On the Speed Versus Accuracy Trade-Off. In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems AAMAS 2015, pag. 1305–1314, IFAAMAS, 2015
    @inproceedings{ValHamDor2015b,
      author      = {Gabriele Valentini and Heiko Hamann and Marco Dorigo},
      title       = {Efficient Decision-Making in a Self-Organizing Robot Swarm: On the Speed Versus Accuracy Trade-Off},
      booktitle   = {Proceedings of the 14th Int. Conf. on Autonomous Agents and Multiagent Systems},
      pages       = {1305--1314},
      year        = {2015},
      editor      = {Bordini, Elkind, Weiss, Yolum},
      series      = {AAMAS '15},
      publisher   = {IFAAMAS}
      }
  10. G. Valentini, D. Brambilla, H. Hamann, M. Dorigo. Collective Perception of Environmental Features in a Robot Swarm. Swarm Intelligence, Proceedings of the Tenth International Conference on Swarm Intelligence ANTS 2016, vol. 9882 of LNCS, pag. 65–76, Springer, 2016
    @inproceedings{ValBraHamDor2016,
      author      = {Gabriele Valentini and Davide Brambilla and 
                     Heiko Hamann and Marco Dorigo},
      title       = {Collective Perception of Environmental Features in a Robot Swarm},
      year        = {2016},
      booktitle   = {Swarm Intelligence},
      pages       = {65--76},
      editor      = {Marco Dorigo and Mauro Birattari and Xiaodong Li and Manuel {L\'opez-Ib\'a\~nez} and Kazuhiro Ohkura and Carlo Pinciroli and Thomas St\"utzle},
      series      = {LNCS},
      volume      = {9882},
      publisher   = {Springer}
      }
  11. H. Hamann, G. Valentini, M. Dorigo. Population Coding: A New Design Paradigm for Embodied Distributed Systems. Swarm Intelligence, Proceedings of the Tenth International Conference on Swarm Intelligence ANTS 2016, vol. 9882 of LNCS, pag. 173–184, Springer, 2016
    @inproceedings{HamValDor2016,
      author      = {Heiko Hamann and Gabriele Valentini and Marco Dorigo},
      title       = {Population Coding: A New Design Paradigm for Embodied Distributed Systems},
      year        = {2016},
      booktitle   = {Swarm Intelligence},
      pages       = {173--184},
      editor      = {Marco Dorigo and Mauro Birattari and Xiaodong Li and Manuel {L\'opez-Ib\'a\~nez} and Kazuhiro Ohkura and Carlo Pinciroli and Thomas St\"utzle},
      series      = {LNCS},
      volume      = {9882},
      publisher   = {Springer}
      }
  12. A. Antoun, G. Valentini, E. Hocquard, B. Wiandt, V. Trianni, M. Dorigo. Kilogrid: a Modular Virtualization Environment for the Kilobot Robot. In Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems IROS 2016, pag. 3809–3814, IEEE Press, 2016
    @inproceedings{AntValHocWiaTriDor2016,
      author    = {A. Antoun and G. Valentini and E. Hocquard and B. Wiandt and V. Trianni and M. Dorigo},
      booktitle = {2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
      pages     = {3809--3814},
      publisher = {IEEE Press},
      title     = {Kilogrid: a Modular Virtualization Environment for the Kilobot Robot},
      year      = {2016}
      }
  13. D.G. Moore, G. Valentini, S.I. Walker, M. Levin. Inform: A Toolkit for Information-Theoretic Analysis of Complex Systems. In Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, Symposium on Artificial Life SSCI 2017, pag. 1–8, IEEE Press, 2017
    @inproceedings{MorValWalLev2017,
      author    = {D.G. Moore and G. Valentini and S.I. Walker and M. Levin},
      booktitle = {2017 IEEE Symposium Series on Computational Intelligence, Symposium on Artificial Life},
      pages     = {1--8},
      publisher = {IEEE Press},
      doi       = {10.1109/SSCI.2017.8285197}, 
      title     = {Inform: A Toolkit for Information-Theoretic Analysis of Complex Systems},
      year      = {2017}
      }
  14. G. Valentini, D.G. Moore, J.R. Hanson, T.P. Pavlic, S.C. Pratt, S.I. Walker. Transfer of Information in Collective Decisions by Artificial Agents. The 2018 Conference on Artificial Life: A Hybrid of the European Conference on Artificial Life (ECAL) and the International Conference on the Synthesis and Simulation of Living Systems (ALIFE) ALIFE 2018, NO. 30, pag. 641–648, MIT Press, 2018
    @inproceedings{ValMorHanPavPraWal2018,
      author    = {G. Valentini and D.G. Moore and J.R. Hanson and T.P. Pavlic and S.C. Pratt and S.I. Walker},
      booktitle = {The 2018 Conference on Artificial Life: A Hybrid of the European Conference on Artificial Life (ECAL) and the International Conference on the Synthesis and Simulation of Living Systems (ALIFE)},
      pages     = {641--648},
      publisher = {MIT Press},
      doi       = {10.1162/isal\_a\_00117},  
      title     = {Transfer of Information in Collective Decisions by Artificial Agents},
      year      = {2018}
      }
  15. M. Trabattoni, G. Valentini, M. Dorigo. Hybrid Control of Swarms for Resource Selection. Swarm Intelligence, Proceedings of the Eleventh International Conference on Swarm Intelligence ANTS 2018, vol. 11172 of LNCS, pag. 57–70, Springer, 2018
    @inproceedings{TraValDor2018,
      author     = {Marco Trabattoni and Gabriele Valentini and Marco Dorigo},
      title      = {Hybrid Control of Swarms for Resource Selection},
      year       = {2018},
      booktitle  = {Swarm Intelligence},
      pages      = {57--70},
      editor     = {Marco Dorigo and Mauro Birattari and Christian Blum and Anders L. Christensen annd Andreagiovanni Reina and Vito Trianni},
      series     = {LNCS},
      volume     = {11172},
      publisher  = {Springer}
      }

Workshops

  1. G. Valentini. Self-Organized Collective Decision-Making in Swarms of Autonomous Robots. In Proceedings of 13th International Conference on Autonomous Agents and Multiagent Systems AAMAS 2014, Doctoral Symposium, pag. 1703–1704, IFAAMAS, 2014
    @inproceedings{Val2014,
      author      = {Gabriele Valentini},
      title       = {Self-Organized Collective Decision-Making in Swarms of Autonomous Robots},
      booktitle   = {Proceedings of the 13th Int. Conf. on Autonomous Agents and Multiagent Systems},
      pages       = {1703--1704},
      year        = {2014},
      editor      = {Alessio Lomuscio and Paul Scerri and Ana Bazzan and Michael Huhns},
      series      = {AAMAS '14},
      publisher   = {International Foundation for Autonomous Agents and Multiagent Systems},
      location    = {Paris, France},
      annote      = {Doctoral Symposium}
      }
  2. H. Hamann, G. Valentini. Micro-Macro Links for Self-Organizing Collective Systems: From Local State Transition Rules to Global Transition Probabilities and Back. In Seventh International Workshop on Guided Self-Organization GSO 2014
  3. A. Reina, G. Valentini, C. Fernández-Oto, M. Dorigo, V. Trianni. A Design Pattern for Best-of-n Collective Decisions. In 3rd Workshop on Biological Distributed Algorithms, BDA 2015
  4. J.R. Hanson, S.I. Walker, G. Valentini, T.P. Pavlic, S.C. Pratt. Incognizant Collective Decision Making in Ant Colonies. In 2018 Southwest Robotics Symposium, SRS 2018
  5. S.K. Ray, G. Valentini, A. Haque, S. Garnier. Information Transfer in the Contractile Membrane of Slime Mold Physarum polycephalum During Decision-Making. In First Northeast Regional Conference on Complex Systems, NERCCS 2018
  6. G. Valentini, S. Zhou, J.R. Hanson, T.P. Pavlic, S.C. Pratt, S.I. Walker. Information Transfer During Tandem-Running Behavior of the Ant Temnothorax rugatulus: Time Scales of Leadership? In International Union for the Study of Social Insects, IUSSI 2018
  7. C.L. Kwapich, G. Valentini, B. Hölldobler. The Non-Additive Effects of Body Size on Nest Architecture in a Polymorphic Ant, Veromessor pergandei. In International Union for the Study of Social Insects, IUSSI 2018
  8. T.P. Pavlic, J.R. Hanson, G. Valentini, S.I. Walker, S.C. Pratt. Quorum Sensing without Counting, a Discounting Approach, or: Nobody Goes There Anymore, It’s Too Crowded. In 6th Workshop on Biological Distributed Algorithms, BDA 2018
  9. S.K. Ray, G. Valentini, P. Shah, A. Haque, S. Garnier. Information Transfer in the Slime Mold Physarum polycephalum Membrane During Decision-Making. In 55th Annual Conference of the Animal Behavior Society, ABS 2018
  10. M.L. Borowiec, G. Valentini, C. Rabeling. A Deep Learning Framework for Identification of North American Ant Genera Using Photographs of Live and Preserved Specimens. In Annual Meeting of the Entomological Society of America, ESA 2018
  11. T.P. Pavlic, J.R. Hanson, G. Valentini, S.I. Walker, S.C. Pratt. Cognition in Physical Spaces: A Quorum-Sensing Mechanism for Ants without Sequential Sampling. In 56th Annual Conference of the Animal Behavior Society and the 36th International Ethological Conference, Behaviour 2019
  12. C.L. Kwapich, G. Valentini, B. Hölldobler. Individual Experience and Polymorphism Shape Ant Nest Architecture. In 56th Annual Conference of the Animal Behavior Society and the 36th International Ethological Conference, Behaviour 2019
  13. G. Valentini, N. Mizumoto, T.P. Pavlic, S.C. Pratt, S.I. Walker. Complex Communication: Receiver-Sourced Signals that Regulate Information Flow During Social Recruitment. In 56th Annual Conference of the Animal Behavior Society and the 36th International Ethological Conference, Behaviour 2019

Scientific Videos

  1. G. Valentini, H. Hamann, M. Dorigo. Self-Organized Collective Decisions in a Robot Swarm. In Video Proceedings of the 9th AAAI Video Competition, AAAI 2015 AAAI Best Student Video Award

Invited Talks

  1. A Novel Approach to Model Selection in Distribution Estimation Using Markov Networks. Institut de Recherches Interdisciplinaires et de Développements en Intelligence Artificielle, Université Libre de Bruxelles, Brussels, Belgium, 2011
  2. Modeling Swarm Intelligence Systems with Markov Chains. Swarm Intelligence Group, Universität Paderborn, Paderborn, Germany, 2013
  3. Efficient Decision-Making in a Self-Organizing Robot Swarm: On the Speed Versus Accuracy Trade-Off. Lab of Socioecology & Social Evolution, Katholieke Universiteit Leuven, Leuven, Belgium, 2015
  4. The Best-of-n Problem in Robot Swarms. Social Insects Research Group, Arizona State University, Tempe, Arizona, USA, 2016
  5. Information Flow in Ant Colony Emigrations, Collective Decisions in Robot Swarms and the Kilogrid System. Autonomous Collective Systems Laboratory, Arizona State University, Tempe, Arizona, USA, 2017
  6. The Best-of-n Problem in Robot Swarms. 2017 International Joint Conference on Artificial Intelligence (IJCAI), Award ceremony for the EurAI Distinguished Dissertation Award, Melbourne, Australia, 2017
  7. Information Transfer in Collective Computation by Ants, Termites, and Slime Molds. Santa Fe Institute, Santa Fe, New Mexico, USA, 2019

Statistics

2017 Innovative Postdoctoral Reaserch Award, SOLS RTI
(2500 USD)
2016 EurAI Artificial Intelligence Distinguished Dissertation Award
(1500 EUR)
2015 AAAI Best Student Video Award
Nomination for
2015 AAMAS Best Paper Award
Nomination for
2014 ANTS Best Paper Award

Peer review activity: