PLENARY / Invited Speakers

Plenary speakers

Marco Dorigo

Université Libre de Bruxelles 

Self-Organizing Nervous System for Robot Swarms 

Robot swarms that are fully self-organized without any central coordinating entity have been widely demonstrated. A robot swarm with a fully decentralized architecture is highly redundant, and its collective behavior results indirectly from local interactions. These characteristics provide frequently cited advantages---including scalability, fault tolerance through redundancy, and having no single point of failure---but also result in fundamental problems, including lack of manageability. By contrast, centralized systems are easy to design, control, and manage, but have single points of failure and limited scalability. In the talk, I will present a novel robot swarm architecture for self-organized hierarchy, combining the advantageous features of self-organized and centralized control. Using a heterogeneous swarm of ground robots and aerial vehicles, I will demonstrate the ability of the proposed robot swarm architecture to self-organize a dynamic hierarchical control network using local asymmetric communication. I will show the results of experiments in which the architecture can split and merge independently controlled sub-swarms, replace faulty robots at any point in the hierarchical network, and modify the collective behavior of the swarm on the fly. I will also demonstrate that the proposed architecture maintains the fundamental advantages of using strict self-organization, including scalability of the swarm and interchangeability of individual robots.


Marco Dorigo received the Ph.D. degree in electronic engineering in 1992 from Politecnico di Milano, Milan, Italy. From 1992 to 1993, he was a Research Fellow at the International Computer Science Institute, Berkeley, CA. In 1993, he was a NATO-CNR Fellow, and from 1994 to 1996, a Marie Curie Fellow. Since 1996, he has been a tenured Researcher of the FNRS, the Belgian National Funds for Scientific Research, and co-director of IRIDIA, the artificial intelligence laboratory of the ULB. His current research interests include swarm intelligence, swarm robotics, and metaheuristics for discrete optimization. He is the Founding Editor of Swarm Intelligence, and an Associate Editor or member of the Editorial Boards of many journals on computational intelligence and adaptive systems. Dr. Dorigo is a Fellow of the AAAI, EurAI, and IEEE. He was awarded the  Italian Prize for Artificial Intelligence in 1996, the Marie Curie Excellence Award in 2003, the Dr. A. De Leeuw-Damry-Bourlart award in applied sciences in 2005, the Cajastur International Prize for Soft Computing in 2007, an ERC Advanced Grant in 2010, the IEEE Frank Rosenblatt Award in 2015, and the IEEE Evolutionary Computation Pioneer Award, awarded in 2016.

Hyo-Sung Ahn

Gwangju Institute of Science and Technology 

Distributed Formation Control Inspired from Collective Behaviors 

The distributed formation control laws use relative information defined in local coordinate frames; thus, from a sensing perspective, the formation control laws are fully distributed. The formation control laws have been mainly used for the control of multi-agent systems, including coordination of a group of mobile agents, formation flying of UAVs, platooning of a group of autonomous vehicles, and rendezvous of spacecrafts. From the perspective that the distributed formation control uses local relative measurements for the control of agents, it could be conjectured that the distributed formation control imitates the feature of collective animal motions. After briefly reviewing the collective behaviors of biological systems, distributed formation control laws are mathematically refined to show how they are related to the animal’s sensing mechanisms. In this talk, we would like to seek for a further opportunity for applying the formation control algorithms to network systems including network localization, and analysis of social and complex networks.


Hyo-Sung Ahn received the B.S. and M.S. degrees in astronomy from Yonsei University, Seoul, South Korea, in 1998 and 2000, respectively, the M.S. degree in electrical engineering from the University of North Dakota, Grand Forks, ND, USA, in 2003, and the Ph.D. degree in electrical engineering from Utah State University, Logan, UT, USA, in 2006. Since July 2007, he has been with the School of Mechatronics and the School of Mechanical Engineering, Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea. He was a Dasan Distinguished Professor (Dasan Professor), from 2013 to 2018. Before joining GIST, he was a Senior Researcher with the Electronics and Telecommunications Research Institute, Daejeon, South Korea. He was a Visiting Scholar with the Colorado School of Mines in 2019. He is currently a Professor with the School of Mechanical Engineering, GIST. Dr. Ahn is a Fellow of ICROS and Senior Member of IEEE, and he is serving as an Editor-in-Chief of International Journal of Control, Automation, and Systems. He is the author of the books Iterative Learning Control: Robustness and Monotonic Convergence for Interval Systems (Springer, 2007), Formation Control: Approaches for Distributed Agents (Springer, 2020), and a co-author of the book Control of Multi-agent Systems: Theory and Simulation with Python (Springer, 2024). His research interests include distributed control, aerospace navigation and control, network localization, and learning control.

Andrew Adamatzky

University of the West of England 

Fungal Neuroscience

Fungi generate neuron-like action potential spikes, akin to neurons. We provide an overview of the emerging field of fungal neuroscience, aiming to create a living fungal brain. Discussing the electrical properties of fungi, we demonstrate, through computer models and experimental studies, their ability to perceive and process information similar to neural networks. Introducing fungal neuromorphic electronics, made from mycelium-bound composites or pure mycelium, we highlight their capability to change impedance and generate electrical spikes in response to external controls. These circuits can be embedded in materials, wearables, or used as standalone sensing and computing devices. The presentation comprises three parts: fungal electronics, fungal computing, and fungal language.

In fungal electronics, we explore devices such as memristors and fungal oscillators. Memristors, crucial in neuromorphic circuits, exhibit memristive properties in P. ostreatus fruit bodies subjected to voltage sweeps. Fungal oscillators utilize endogenous fluctuations in mycelium-bound composite electrical resistance. Tactile sensing experiments with fungal blocks reveal their ability to distinguish weight application and removal through distinct amplitude and duration spikes. Optical and chemical fungal sensors respond to illumination and chemical stimuli, respectively, showcasing unique patterns of electrical activity.

Fungal computing involves electrical analog and voltage spike-based approaches. In numerical modeling and laboratory setups, we apply electrical analog computing principles, representing logical values with above and below threshold voltages. Fungal colonies maintain integrity through cytoplasmic flow and coordination of mycelium tips, controlled by waves of electrical potential. These waves enable voltage spike-based computations in mycelium networks, demonstrated through numerical modeling and logical gate implementation.

Fungal language is introduced based on oscillations of extracellular electrical potential in various fungi. Analyzing electrical activity in O. nidiformis, F. velutipes, S. commune, and C. militari, we observe clustered spikes. Assuming fungal spikes are used for communication and information processing, we group them into words, conducting linguistic and information complexity analyses. Fungal word length distributions mirror human languages. Algorithmic and Liz-Zempel complexity hierarchies of fungal sentences are constructed, advancing our understanding of fungal language syntax. 


Andrew Adamatzky is Professor of Unconventional Computing and Director of the Unconventional Computing Laboratory, Department of Computer Science, University of the West of England, Bristol, UK. He does research in molecular computing, reaction-diffusion computing, collision-based computing, cellular automata, slime mould computing, massive parallel computation, applied mathematics, complexity, nature-inspired optimisation, collective intelligence and robotics, bionics, computational psychology, non-linear science, novel hardware, and future and emergent computation.

He has authored seven books, mostly notable are Reaction-Diffusion Computing, Dynamics of Crow Minds, and Physarum Machines, and has edited 22 books in computing, most notable are Collision-Based Computing, Game of Life Cellular Automata, and Memristor Networks. He has also produced a series of influential artworks published in the atlas Silence of Slime Mould. He is Founding Editor-in-Chief of Journal of Cellular Automata and Journal of Unconventional Computing and Editor-in-Chief of Journal Parallel, Emergent, Distributed Systems and Parallel Processing Letters.

Takao Sasaki

University of Georgia 

Collective learning in ant colonies 

Humans are known for sharing and accumulating knowledge in a group over time, a phenomenon known as collective learning. Many other species also form groups and face the same tasks together repeatedly so that their collective performance can be positively influenced by information acquired from past experiences. However, the field of animal learning has mainly focused on individual learning but directed little attention to learning by multiple entities. As a result, researchers study learning abilities of social animals in isolated conditions, assuming that collective learning is nothing more than the sum of the respective learnings by the group members. I will discuss if and how groups attain synergetic and advantageous performance using ant colonies. By carrying multidisciplinary—behavioral ecology, psychology, anthropology, physics and mathematics—investigation, my research will ultimately shed new light on our understanding of benefits and mechanisms of learning as a group.


Takao Sasaki is an Assistant Professor in the Odum School of Ecology at the University of Georgia. He received a B.S. degree in Physics from Nihon University, Tokyo, Japan, in 2002 and a M.S. degree in Psychology and a Ph.D. degree in Biology from Arizona State University, Tempe, AZ, USA, in 2008 and 2013, respectively. He was a Royal Society Newton Postdoctoral Fellow (2014-2016) and a Marie Skłodowska-Curie Postdoctoral Fellow (2016-2018) at Oxford University, Oxford, UK. His research interests include collective decision making, collective cognition, and coordinated behavior.

Invited speakers

Kazuki Tsuji 

University of the Ryukyus  

“Social cancers” in cooperative ant societies 

Cooperation and conflicts are ubiquitous in insect societies. While the cooperation of individuals is the main driver of the ecological success of social insects, colonies are always threatened by invasion of exploiters from the outside such as conspecific and heterospecific competitors and social parasites. Also, from inside colonies genetic mutation can generate cheaters or freeriders that exploit the colony’s public goods without paying personal cost for cooperation. Such relationships seem to be general across biological hierarchies when functional integration of units is recognized. For example, like immunity protects individual organisms from enemies such as pathogens and mutant cancer cells, insect societies also show protection from exploitation. Membership discrimination limits invasion from the outside and policing discourage selfish behavior of colony members. Those can be regarded as “immunity of society”. Also, as many individual organisms are killed by infectious disease and cancers in the real world despite immunity, social immunity is imperfect and in nature many insect colonies are damaged by various kinds of exploiters from the outside and inside. 

To study an “exploiter of society from the inside” I focus on the parthenogenetic ant, Pristomyrmex punctatus, that is characterized by an intraspecific social parasitism by genetically determined “cheater” lineages or “social cancers”. Our previous laboratory experiments showed that cheaters outcompeted coexisting workers (cooperators) in both survival and reproduction, although a group composed only of cheaters failed to produce offspring, which fits to the situation of the public goods dilemma. The coexistence of cheaters and cooperators in the field makes direct observation of micro-evolutionary dynamics possible. We measured multilevel selection operating in a field population and showed that the short-term evolutionary changes follow the prediction of kin and group selection models. Cheaters are increasing in the proportion to the entire population in the short term. This is the only empirical test of those social evolution theories with direct observation of evolutionary change in the field. We extend our scope concerning this system to consequences on the community-level, or eco-evolutionary feedback.


Present Occupation: Professor

Affiliation: Department of Agro-Environmental Sciences, Faculty of Agriculture, University of the Ryukyus, and the United Graduate School of Agricultural Sciences, Kagoshima University

Education: 1986-1989: Doctorate Course of Research Division of Agriculture, Graduate School of Nagoya University (PhD, 1989)

Professional Career: 

Specialty: Animal Ecology, Behavioral Ecology, Evolutionary Biology


Professional services:

Azusa Kamikouchi

Nagoya University 

Acoustic communication in Fruit flies and Mosquitoes 

Various animals, ranging from humans to birds to insects, use sounds to communicate during mating rituals within their species. In the case of fruit flies, males produce courtship songs through wing vibrations to attract females. On the other hand, mosquito males detect a faint flight tone emitted by nearby females, triggering a phonotactic attraction towards them in a swarm. However, the mechanism by which these small insects can detect and evaluate the sounds emitted by potential mating partners in a noisy environment is not well understood. In this talk, I will first introduce how they perceive sounds. Then, I will share our recent findings on the neural mechanisms of their auditory systems that support acoustic communication between males and females.


Azusa Kamikouchi is a professor in the Graduate School of Science at Nagoya University. She earned her PhD from the University of Tokyo, Japan, in 2002, where she participated in a project under the guidance of Prof. Takeo Kubo to unravel the neural basis of honeybees’ social behaviors. Subsequently, she served as a postdoctoral researcher in Prof. Kei Ito’s lab, investigating the anatomical and functional organization of the auditory system of fruit flies. This research took place initially at the National Institute for Basic Biology and later at the University of Tokyo, Japan. To further develop this understanding, she relocated to the University of Cologne in Germany to join Prof. Martin C. Göpfert’s group (now in Göttingen). In 2008 she took on the role of assistant professor at Tokyo University of Pharmacy and Life Sciences, Japan. She later moved to Nagoya University in 2011, where she currently holds a full professorship.


Tohoku University 

Investigating Control Principle Underlying Animal Locomotion: A Tegotae-based Control Approach 

Animals self-organize surprisingly adaptive and resilient behavior under real world constraints. Such behaviors are achieved via real-time spatiotemporal coordination between a large number of bodily degrees of freedom in response to the situation. Clarifying the control principle behind this remarkable ability of animals allows us to understand biological systems more deeply as well as to construct truly adaptive robot that could not be realized solely by the conventional robotics methodology. In this talk, I will present a series of our challenges for decoding the control principle behind various types of animal locomotion, and I will then show that our model called Tegotae-based control could be a key to understanding such control principle. I will also present our recent projects aiming at extending Tegotae-based control for investigating locomotion of not only extant animals but also extinct animals.


Akio Ishiguro received B.E., M.E., and Ph.D. degrees from Nagoya University in 1987, 1989, and 1991, respectively. From 1991 to 1997, he served as an assistant professor at Nagoya University. From May 1997 to 2006, he served as an associate professor at Nagoya University. From 2006 to 2011, he was a professor of the Graduate School of Engineering, Tohoku University. Since April 2011, he has been a professor of Research Institute of Electrical Communication, Tohoku University. His main research interests are in robotics-inspired biology, mathematical biology, nonlinear dynamics. He received IROS Best Paper Award Nomination Finalist (2003 and 2009), IROS Best Paper Award (2004), Ig Nobel Prize (Cognitive Science Prize) (2008), IROS NTF Award Finalist for Entertainment Robots and Systems (2011). IROS JTCF Novel Technology Paper Award Finalist (2012). Living Machines Best Paper Award (2012), WIRED Audi Innovation Award (2016), IROS Best Paper Award on Cognitive Robotics Finalist (2020).