Postdoctoral Positions at the Center for Network Dynamics, Northwestern University

The newly launched Center for Network Dynamics at Northwestern University is actively seeking postdoctoral researchers interested in complex systems and networks. We welcome applications from individuals with expertise in various aspects of network theory, including temporal, multilayer, and higher-order interactions. Additionally, we are seeking applicants with interest in network modeling of biological, physical, and engineering systems. The projects are theoretical and computational but benefit from empirical data and close collaborations with experimental colleagues. If you are passionate about advancing the understanding of networks and their applications in diverse fields, we encourage you to apply to our dynamic research team. For information on how to apply, please visit cnd.northwestern.edu

French Regional Conference on Complex Systems FRCCS 2024. May 29-31, Montpellier, France

FRCCS 2024 is the 4th edition of the French Regional Conference on Complex Systems. It aims at bringing together the French scientific community working in complex systems. It intends to federate the French community.
We encourage researchers from various disciplines supporting interdisciplinary exchanges to respond to this call (archaeology, biology, computer science, economics, geography, history, linguistics, management, mathematics, medicine, physics, statistics, sociology, …). FRCCS 2024 is an opportunity to promote the cross-fertilization of ideas by presenting recent research work, industrial developments, and original applications. Special attention is given to research topics with a high societal impact from the perspective of complexity science from the complexity science perspective.

More at: iutdijon.u-bourgogne.fr

Towards self‐organizing logistics in transportation: a literature review and typology

Berry Gerrits, Wouter van Heeswijk, Martijn Mes

Intl. Trans. in Op. Res. 0 (2023) 1–66

Deploying self-organizing systems is a way to cope with the logistics sector’s complex, dynamic, and stochastic nature. In such systems, automated decision-making and decentralized or distributed control structures are combined. Such control structures reduce the complexity of decision-making, require less computational effort, and are therefore faster, reducing the risk that changes during decision-making render the solution invalid. These benefits of self-organizing systems are of interest to many practitioners involved in solving real-world problems in the logistics sector. This study, therefore, identifies and classifies research related to self-organizing logistics (SOL) with a focus on transportation. SOL is an interdisciplinary study across many domains and relates to other concepts, such as agent-based systems, autonomous control, and decentral systems. Yet, few papers directly identify this as self-organization. Hence, we add to the existing literature by conducting a systematic literature review that provides insight into the field of SOL. The main contribution of this paper is two-fold: (i) based on the findings from the literature review, we identify and synthesize 15 characteristics of SOL in a typology, and (ii) we present a two-dimensional SOL framework alongside the axes of autonomy and cooperativity to position and contrast the broad range of literature, thereby creating order in the field of SOL and revealing promising research directions.

Read the full article at: onlinelibrary.wiley.com

A blockchain-based information market to incentivise cooperation in swarms of self-interested robots

Ludéric Van Calck, Alexandre Pacheco, Volker Strobel, Marco Dorigo & Andreagiovanni Reina
Scientific Reports volume 13, Article number: 20417 (2023)

Robot swarms are generally considered to be composed of cooperative agents that, despite their limited individual capabilities, can perform difficult tasks by working together. However, in open swarms, where different robots can be added to the swarm by different parties with potentially competing interests, cooperation is but one of many strategies. We envision an information market where robots can buy and sell information through transactions stored on a distributed blockchain, and where cooperation is encouraged by the economy itself. As a proof of concept, we study a classical foraging task, where exchanging information with other robots is paramount to accomplish the task efficiently. We illustrate that even a single robot that lies to others—a so-called Byzantine robot—can heavily disrupt the swarm. Hence, we devise two protection mechanisms. Through an individual-level protection mechanism, robots are more sceptical about others’ information and can detect and discard Byzantine information, at the cost of lower efficiency. Through a systemic protection mechanism based on economic rules regulating robot interactions, robots that sell honest information acquire over time more wealth than Byzantines selling false information. Our simulations show that a well-designed robot economy penalises misinformation spreading and protects the swarm from Byzantine behaviour. We believe economics-inspired swarm robotics is a promising research direction that exploits the timely opportunity for decentralised economies offered by blockchain technology.

Read the full article at: www.nature.com