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        <title>Frontiers in Complex Systems | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/complex-systems</link>
        <description>RSS Feed for Frontiers in Complex Systems | New and Recent Articles</description>
        <language>en-us</language>
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        <pubDate>2026-10-21T23:38:50.129+00:00</pubDate>
        <ttl>60</ttl>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1887490</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1887490</link>
        <title><![CDATA[Emergent socioecological dynamics in Eastern Polynesian chiefdoms: a comparative network analysis of the Society and Gambier Islands]]></title>
        <pubdate>2026-10-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Jennifer G. Kahn</author><author>Stefani A. Crabtree</author><author>Patrick V. Kirch</author><author>Abigail Buffington</author><author>Spencer A. Wood</author><author>Dieta Hanson</author><author>Evan Holt</author><author>Jennifer A. Dunne</author>
        <description><![CDATA[Methods from complexity science can help us better understand the development of socioecological systems. Here we investigate how human relationships with diverse species were structured through ecological and cultural networks in the Society Islands and the Gambier Islands, two archipelagoes of Central Eastern Polynesia. Each archipelago was settled by voyaging societies derived from similar ancestry concomitantly experiencing European contact, thus having remarkably short c. 800–900-year pre-contact cultural sequences. These short cultural sequences allow us to examine how similar cultures colonized contrastive, yet pristine island ecosystems with similar imported taxa and cultural principles yet ended up with social systems of differing socio-political complexity some 800–900 years later. To investigate these dynamics, we apply the “Human Interactions with Other Species” (HIOS) network analysis to archaeological, ethnographic, and historical evidence of human engagement with local and introduced taxa. Rather than framing sociopolitical change as the product of either environmental constraints or cultural agency alone, our analysis emphasizes the development of social and ecological systems together through time. The results demonstrate that differences in biodiversity structure, resource availability, and interspecies interactions influenced subsistence practices, material production, and social organization, while also highlighting the importance of local social dynamics in mediating ecological constraints. A secondary finding is methodological: correspondence analysis, a tool long used in anthropology, produces patterns broadly consistent with those identified through network analysis, while network analysis additionally reveals structural relationships that correspondence analysis cannot capture. More broadly, this study illustrates how comparative socioecological network analysis can contribute to understanding historical dynamics in island societies and demonstrates the value of complex systems approaches for examining cultural diversification in Polynesia.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1920737</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1920737</link>
        <title><![CDATA[Surviving by Serving - the effects of rewarding usefulness]]></title>
        <pubdate>2026-10-15T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Patrick Krauss</author><author>Ali Ghebleh</author><author>Achim Schilling</author><author>Andreas Maier</author><author>Thomas Kinfe</author><author>Claus Metzner</author>
        <description><![CDATA[How can a complex production network organize itself when no participant knows the global plan? We investigate a simple principle inspired by markets: producers persist longer when what they make is actually used. We call this principle “Surviving by Serving” (SbS). In a deliberately minimal model, agents transform existing products into new ones and thereby build fluctuating production and supply networks starting from a single inexhaustible resource. We compare SbS with systems in which survival is not rewarded and with a control in which the same reward events are redirected to randomly selected agents. Within the tested model and parameter ranges, linking survival to downstream use enables faster and broader exploration of product space while retaining a larger share of what has been discovered. It also gives rise to more persistent, repeatedly active production pathways and more pronounced cyclic structures. In a targeted-reward experiment, selectively supporting suppliers of designated products can increase delivery to the desired region, without specifying the supply chains needed to reach it. These results do not establish a universal law of self-organization. They show, however, that a minimal local feedback between usefulness and persistence can substantially reshape collective organization in this model and motivate tests of analogous mechanisms in richer economic and biological networks.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1868587</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1868587</link>
        <title><![CDATA[Detecting historical turning points in Italian media: a complex systems approach to a diachronic news corpus]]></title>
        <pubdate>2026-10-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Dario Zarcone</author><author>Salvatore Miccichè</author><author>David Sánchez</author>
        <description><![CDATA[IntroductionThe increasing availability of large-scale textual corpora has opened new possibilities for data-driven, quantitative approaches to historical analysis using Natural Language Processing (NLP). However, diachronic corpora with historical relevance from the pre-digital era remain scarce and often incomplete.MethodsWe present a quantitative approach to historical analysis based on the reconstruction and exploration of a diachronic corpus of around 600,000 articles from the Italian newspaper “La Repubblica”, covering all the articles published from the first of January 1985 to the 31st of December 2000 - a period of major political, social, and geopolitical change in Italy and globally. Using NLP techniques, we analyze the text at both lexical and semantic levels; we then apply tools from complex systems and statistical physics to trace shifts in media discourse over time.ResultsThe word usage in the corpus is bursty, with a heavy-tailed distribution of Fano factors that is robust across timescales. Changepoints in word salience and the block structure of semantic similarity allow us to detect key transition periods, such as the transition from the First Republic to the Second Republic in Italy, or major international conflicts like the Gulf War or the Kosovo War, without relying on prior labeling. Periods of war correspond to lower entropy in the semantic space, indicating a more focused discourse.DiscussionThe results show how combining computational linguistics with ideas from complex systems can offer new quantitative insight into historical changes, opening up new paths for studying the dynamics of media and society through large-scale textual data.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1853769</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1853769</link>
        <title><![CDATA[The straw and the Camel’s Back: tempo governance in an age of invisible erosion]]></title>
        <pubdate>2026-09-25T00:00:00Z</pubdate>
        <category>Hypothesis and Theory</category>
        <author>Natalie Avneri Rosen</author>
        <description><![CDATA[Every culture has a version of the same story: the straw that broke the camel’s back, the drop that overflowed the cup, the last grain that toppled the pile. These idioms encode an ancient intuition that collapse is not caused by the final input but by everything that preceded it invisibly. Yet the dominant frameworks for understanding systemic failure continue to focus on the straw. The trigger. The shock. The proximate cause. The Capacity-Load Mismatch (CLM) framework, developed across the preceding three papers in this series, provides a formal account of what happens to the back before the straw arrives. Regulatory margin erodes under tempo-weighted load, following a dynamical trajectory that produces critical slowing down, hysteresis, and a characteristic perceptual trap termed the Linear Illusion, in which conventional metrics remain stable while the system’s distance from collapse shrinks to near-zero. This paper applies the CLM framework to three domains of contemporary systemic stress: healthcare systems under pandemic surge, cognitive architecture under digital acceleration, and democratic institutions under information overload. In each case, the post-hoc narrative attributed failure to the triggering event. The CLM analysis identifies a longer history, one of tempo-driven margin erosion that conventional monitoring could not detect. These case studies are analytical applications, reinterpretations of well-documented phenomena through a formal lens, rather than empirical tests, which will require dedicated domain-specific investigation. From this analysis, I derive two governance principles, Capacity First Design and Tempo Governance, and propose the Tempo Audit, a structured diagnostic framework derived from the CLM model’s formal variables that enables systems at any scale to assess their proximity to collapse before the straw arrives. I conclude with the argument that modernity’s central project, the optimization of throughput and the elimination of idle time, constitutes a systematic reduction of the regulatory margin that keeps complex systems viable.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1830387</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1830387</link>
        <title><![CDATA[Selling on your own land: emergence and self-organization of innovations among small-scale coffee producers to sell in the Mexican domestic market]]></title>
        <pubdate>2026-09-09T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Trinidad Cristina Guerrero Jiménez</author><author>José Miguel Gómez Vargas</author><author>Obeimar Balente Herrera Hernández</author><author>Luis Martínez Villanueva</author>
        <description><![CDATA[This study examines the transition of small-scale producer organizations (SPOs) of fair-trade coffee toward the domestic Mexican market, articulating the Localized Agri-Food Systems (SIAL) approach and complex adaptive systems theory to identify elements of competitive advantage. The methodology employed a sequential mixed-methods design incorporating data mining (12,253 reviews from 148 coffee shops across 8 cities) and participant observation (39 site visits and 4 cupping sessions with 4 SPOs). The main findings indicate that territorial embeddedness constitutes the most relevant factor (up to 61% in Oaxaca), with large effect sizes (η2p ranging from 0.17 to 0.22). Cooperation is not statistically significant, operating instead as an invisible underlying process. Oaxaca exhibits the most consolidated SIAL, with the strongest correlation between collective resource activation and the emergence of innovations (CRA-EI), whereas Tijuana constructs origin narratives through specialized demand. Intermediate projects functioned as living laboratories, generating innovations in quality criteria, service practices, and narratives. Self-organization manifested in the spontaneous reconfiguration of roles (producers as educators, baristas as evaluators). The most relevant second-order learning consisted in recognizing market heterogeneity, identifying differentiated niches (specialty, intermediate, traditional) and new strategic roles. It is concluded that SPO competitiveness is associated with the articulation of an integrated system of actors, resources, narratives, and innovations that anchor coffee to its territory, thereby humanizing the value chain to establish an emotional connection with the consumer. This research contributes theoretically by integrating the SIAL approach with complex adaptive systems theory and introducing the notion of a “value ceiling”; methodologically, by providing a replicable protocol combining data mining, participant observation, and co-construction workshops; and empirically, by documenting the territorial heterogeneity of the Mexican coffee market.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1812652</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1812652</link>
        <title><![CDATA[Towards community-scale resilience via repurposable computing continuum infrastructures]]></title>
        <pubdate>2026-08-11T00:00:00Z</pubdate>
        <category>Hypothesis and Theory</category>
        <author>Nikil Dutt</author><author>Julio A. de Oliveira Filho</author><author>Francesca Palumbo</author><author>Francesco Regazzoni</author><author>Nalini Venkatasubramanian</author>
        <description><![CDATA[Smart cities rely on Cyber Physical Human Systems (CPHS) for efficiently delivering critical services (water, electricity, weather, traffic, etc.) to the community. These community-scale CHPS typically rely on an edge-fog-cloud computing continuum spanning multiple abstraction levels, and are typically purpose-built to deliver these services. This article makes the case that these siloed CPHS can be repurposed to deliver additional services in the face of disasters and unexpected events, raising the overall resilience of these community-scale infrastructures. We use two motivating CPHS case studies–information exchange for healthcare resilience (NSF project CAREDEX) and community-scale urban mobility through end-to-end orchestration (EU project MYRTUS) – as exemplars to tease out the opportunities and challenges faced in repurposing these CHPS in extreme events such as disasters. We highlight some of the key technologies required to facilitate repurposing, summarize their current status, and discuss ongoing efforts and future challenges for achieving community-scale CPHS resilience.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1919371</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1919371</link>
        <title><![CDATA[Correction: Decentralized coordination of autonomous agents in the Compute Continuum using consensus]]></title>
        <pubdate>2026-08-10T00:00:00Z</pubdate>
        <category>Correction</category>
        <author>Xavier Casas-Moreno</author><author>Komal Thareja</author><author>Pablo de Juan Vela</author><author>Rajiv Mayani</author><author>Josep Fanals-i-Batllori</author><author>Anirban Mandal</author><author>Ewa Deelman</author><author>Rosa M. Badia</author><author>Francesc Lordan</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1856624</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1856624</link>
        <title><![CDATA[Winter workshop on complex systems: more than a decade of self-organised community building in complexity research]]></title>
        <pubdate>2026-07-21T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Natalia Briñas-Pascual</author><author>Pablo Rosillo-Rodes</author>
        <description><![CDATA[Every winter for the past 11 years, young researchers from across disciplines and around the world have gathered to explore complexity science and to collaborate intensively on self-organised projects. What began in 2015 as a gathering of colleagues who had first met at a previous workshop at the Santa Fe Institute has since consolidated into a self-organised, resilient workshop for early-career scientists in the complexity community. The Winter Workshop on Complex Systems is characterised by its format: participants form interdisciplinary teams and spend a week developing projects of their own design. By maintaining an economical model that serves as a low-cost alternative to expensive traditional conferences, the workshop prioritises inclusion, ensuring that financial constraints do not prevent talented early-career researchers from participating. This approach not only promotes collaboration and the exchange of ideas but also helps to build a strong, supportive community of young researchers. Many of these collaborations have endured well beyond the workshop, leading to successful publications and long-term partnerships and friendships.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1838587</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1838587</link>
        <title><![CDATA[Time as event: bridging explicit and emergent temporal representations in computer-based social simulations ]]></title>
        <pubdate>2026-07-07T00:00:00Z</pubdate>
        <category>Hypothesis and Theory</category>
        <author>Juan A. Barceló</author><author>Joaquim Fort</author><author>Albert García Piquer</author><author>Olga Palacios</author><author>Ramón Buxó</author><author>Jaume Noguera</author>
        <description><![CDATA[Time is a fundamental yet conceptually undertheorized dimension in computational simulations of historical processes. This paper addresses the problem of temporal representation in these social models by distinguishing two types of temporal information—explicit and emergent—and suggests a formal definition of the temporal event as the primary unit of analysis in a unifying framework for both. In explicit-time models—such as reaction-diffusion systems calibrated against georeferenced calendar dates—time enters as an independent variable governed by differential equations, enabling rigorous testing of temporal sequences that in some circumstances may be consistent with causal hypotheses about the rate, direction, and intensity of social change. In emergent-time models—typically agent-based simulations governed by iterative cycles—temporality arises endogenously from local interactions, adaptive feedback, and cumulative system transformations, revealing how processes may have unfolded mechanistically without imposing predetermined chronological constraints. Our main point is that this difference has profound implications for determining what counts as an assumption and what counts as a result. It also determines the ability to compare computational models of social dynamics with historical empirical evidence. All along the paper, we use the origins of early farming communities in the Prehistoric Mediterranean as a case study for a comparative analysis to reveal critical differences in the way time and space are used as parameters or as emergent dynamics, and their methodological and epistemological consequences.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1800335</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1800335</link>
        <title><![CDATA[Kiso: a foundation for complex, agentic, and reproducible experiments]]></title>
        <pubdate>2026-07-06T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Rajiv Mayani</author><author>Karan Vahi</author><author>Mats Rynge</author><author>Komal Thareja</author><author>Xavier Casas-Moreno</author><author>Hongwei Jin</author><author>Anirban Mandal</author><author>Francesc Lordan</author><author>Krishnan Raghavan</author><author>Rosa M. Badia</author><author>Ewa Deelman</author>
        <description><![CDATA[Experimentation on distributed, heterogeneous computing environments—from edge devices to large-scale cloud platforms—demands orchestration technologies that are both flexible and extensible. Kiso is an open-source framework designed to provision resources and manage complex scientific workflows across the edge-to-cloud continuum. Its architecture unifies infrastructure provisioning, experiment configuration, and reproducible execution, enabling researchers to compose and monitor experiments that span geographically dispersed sites and variable network conditions. Although Kiso was conceived for workflow management—coordinating data-intensive tasks and ensuring reproducibility across dynamic infrastructures—its modular design makes it equally promising for providing reproducible environments for deploying and studying emerging agentic frameworks, where autonomous AI agents require consistent resource provisioning, cross-site communication, and result collection. We describe Kiso’s core capabilities for resource orchestration, experiment lifecycle management, and integration with containerized services, and we outline how these capabilities can support distributed multi-agent systems. In particular, we discuss how its declarative provisioning, extensible task abstractions, and built-in monitoring and output collection provide a natural foundation for experiments in which reasoning agents plan, negotiate, and adapt in real time. This study situates Kiso at the intersection of scientific workflow management and complex, agent-based computing, highlighting its potential to accelerate research on adaptive, self-organizing cyber-physical systems—an emerging frontier in complex systems science.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1819789</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1819789</link>
        <title><![CDATA[A theory of algorithmic markets]]></title>
        <pubdate>2026-06-23T00:00:00Z</pubdate>
        <category>Hypothesis and Theory</category>
        <author>Nagwan Alqershi</author><author>Ramayah Thurasamy</author>
        <description><![CDATA[This paper develops a dynamic framework for analyzing markets in which decision-making is increasingly delegated to adaptive algorithms. In contrast to classical approaches that treat equilibrium as the primitive object of analysis, the framework models markets as systems of interacting learning processes operating within endogenous informational environments. Market outcomes arise from the interaction between adaptive decision rules, endogenous data generation, and feedback amplification. The analysis shows that market stability depends jointly on learning responsiveness and feedback intensity. When adaptive updating is sufficiently regular and feedback effects remain weak, the system converges toward stable equilibrium-like behavior, nesting standard equilibrium models as limiting benchmark cases. As learning responsiveness and endogenous feedback increase jointly, however, the adaptive process may generate persistent fluctuations, endogenous volatility, oscillatory dynamics, and local instability. Equilibrium therefore emerges not as a maintained assumption, but as a possible limiting outcome of the underlying learning dynamics. The framework further implies an adaptation-stability trade-off: faster responsiveness may improve information processing and adjustment while simultaneously amplifying endogenous instability. The analysis also shows how decentralized adaptive interaction may generate synchronized or coordinated patterns of behavior without explicit communication. A stylized quantitative illustration demonstrates how the interaction between learning and feedback shapes distinct dynamic regimes, while an illustrative empirical application to algorithmic trading environments documents patterns broadly consistent with the amplification mechanisms emphasized by the theory. The empirical evidence is interpreted as suggestive rather than definitive causal confirmation. More broadly, the paper suggests that understanding algorithmic markets may require analytical approaches that place adaptive learning, endogenous information generation, and feedback dynamics at the center of economic analysis.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1801157</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1801157</link>
        <title><![CDATA[SWEET: serving workload-balanced end-to-end efficient and tailored edge inference via quantization and partitioning]]></title>
        <pubdate>2026-06-04T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Xiangchen Li</author><author>Saeid Ghafouri</author><author>Hans Vandierendonck</author><author>Deepu John</author><author>Dimitrios S. Nikolopoulos</author>
        <description><![CDATA[We present SWEET, an end-to-end, accuracy-aware inference serving system that tailors execution to heterogeneous edge devices under diverse hardware constraints. Rather than deploying a single fixed pre-trained model for all future queries, serving workload-balanced end-to-end efficient and tailored edge inference (SWEET) plans a request-specific inference pattern by co-optimizing the model configuration and the device–server workload split according to the device’s compute capacity, accuracy requirements, and time constraints. At its core, SWEET integrates joint model quantization and inference partitioning: upon receiving an inference request, the server dynamically provides a quantized model and adaptively shares computation with the edge device, while the system determines the partition point and quantization settings based on the available device computation, channel capacity, and target accuracy. To enable principled decision making, we introduce a unified optimization framework that jointly selects layer-wise quantization bitwidths and partition points to minimize overall time and cost while explicitly accounting for task-dependent accuracy requirements through an accuracy degradation metric in the optimization model. To our knowledge, SWEET is the first inference serving system to optimize layer-wise quantization bitwidth using a theoretical measurement of accuracy degradation. Simulation results demonstrate substantial reductions in end-to-end time and power consumption, achieving a greater than 80% reduction in communication payload while keeping accuracy degradation below 1%.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1808634</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1808634</link>
        <title><![CDATA[Complex systems vs. complex adaptive systems: why the difference matters]]></title>
        <pubdate>2026-05-15T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Shade T. Shutters</author><author>Kelle Dhein</author>
        <description><![CDATA[Terms such as “complexity,” “complex systems,” and “complex adaptive systems” have moved rapidly from specialist research into the vocabularies of policy, sustainability practice, business, and health. Governments now speak of complex adaptive policy systems, funders call for complexity science, and consultants market “complexity thinking” as a way to make sense of polycrises and interlocking risks. Yet underlying this welcome diffusion is a persistent ambiguity. In the research literature, complex systems (CS) and complex adaptive systems (CAS) are related but distinct concepts: all CAS are complex systems, but not all complex systems are adaptive. Outside of academia, however, these terms are often used interchangeably. In this Perspective we clarify the difference between CS and CAS for audiences who are adopting complexity ideas in their own work. We define complex systems as many-component systems with nonlinear interactions and emergent behavior, and complex adaptive systems as the subset in which agents or institutions adapt or learn from experience. We then show how this conceptual distinction maps onto typical examples (weather vs. cities) and onto modeling approaches, such as system dynamics versus agent-based modeling. A concise table summarizes the main contrasts. Finally, we argue that being explicit about CS versus CAS can improve model selection, literature synthesis, and the design of interventions in policy, sustainability, and governance. Rather than proposing new theory, our goal is practical: to help researchers and practitioners understand what they are actually adopting when they invoke “complexity thinking,” and what its limits are in different settings.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1749741</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1749741</link>
        <title><![CDATA[Deliberative project design for understanding and working within complexity in agricultural systems]]></title>
        <pubdate>2026-04-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Hanabeth Luke</author><author>Catherine Allan</author><author>Penny Cooke</author><author>Sarina Kilham</author><author>Alison Ollerenshaw</author><author>Nathan Craig</author><author>Naomi Scholz</author><author>Diana Fear</author><author>Simon Kruger</author><author>Joshua Telfer</author><author>Mathew Alexanderson</author><author>David Davenport</author><author>Yvonne Haigh</author><author>Shae Brown</author><author>Kelly Angel</author>
        <description><![CDATA[New innovations have the potential to improve agricultural resilience, profitability, sustainability and regenerative potential. However, new technologies and approaches emerge in a complex sociocultural context, with farmer decisions based on a range of interacting social, economic and environmental factors. Traditional approaches to research and development within agri-food systems often assume continuity and/or linearity in change processes, which is rarely the case in practice. There are calls for approaches and methods to research and development that can apply deliberative and participatory processes to enable social learning and innovation while embracing inherent complexities. Through a reflection process relating to two multi-stakeholder, collaborative, soils-focused agri-food research projects in Australia, this paper explores how agricultural research projects can navigate and work with complexity. The first project is a national Rural Landholder Social Benchmarking Study, aimed at collecting and drawing together complex data on farmer decision-making around adoption of innovations; and the second is a Knowledge-Sharing Project aimed at improving farmer engagement in new technologies and innovation across Australian farming regions. Our reflective analysis, based on exploring how complexity principles are enacted in these two projects, illustrates how projects can be developed along self-organising principles, developing team capacity to continually learn together and respond to the unexpected. Considering the complex elements of these projects, and how they have operated, opens a pathway for deliberative design that embraces complexity, which may assist the agricultural sector in the development of future research and project management.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1800101</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1800101</link>
        <title><![CDATA[Decentralized coordination of autonomous agents in the Compute Continuum using consensus]]></title>
        <pubdate>2026-04-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Xavier Casas-Moreno</author><author>Komal Thareja</author><author>Pablo de Juan Vela</author><author>Rajiv Mayani</author><author>Josep Fanals-i-Batllori</author><author>Anirban Mandal</author><author>Ewa Deelman</author><author>Rosa M. Badia</author><author>Francesc Lordan</author>
        <description><![CDATA[The Compute Continuum—spanning IoT, Edge, Cloud, and HPC resources—is reshaping how hyper-distributed applications are designed and orchestrated. Traditional service orchestrators and workload management systems rely on centralized runtimes; however, the emerging paradigm requires decentralized coordination, where autonomous agents cooperate to achieve common goals and dynamically distribute workloads. Consensus algorithms play a crucial role in multi-agent systems (MAS), as they enable agents to reach agreement on how to coordinate and execute functionalities in a cooperative manner. While consensus has previously been applied to distributed job selection, here we extend its use to swarm environments. In this setting, agents autonomously decide which service functionalities (i.e., roles) to execute based on their capabilities and the real-time quality of service (QoS). Functionalities can be elastically activated or terminated as application needs evolve. To support this model, we leverage the COLMENA framework, a programming environment for defining and managing such dynamic services. We apply a greedy consensus-based approach to modern power systems, which are increasingly decentralized due to the large-scale integration of renewable energy sources. Centralized power plants are giving way to distributed, intermittent resources that require decentralized control paradigms. To demonstrate this, we simulate the Northeastern Power Coordinating Council’s (NPCC) 140-bus grid using the ANDES simulator in conjunction with the COLMENA middleware. We deploy this use case across six different sites in the FABRIC testbed, using up to 60 different nodes. Our results show that, under contingency scenarios such as load and generator disconnections, agents self-organize, elect local leaders, and execute optimization algorithms to stabilize grid frequency. Detection and organization times remain below 10s across all experiments, even as the number of agents per area scales from 3 to 10. Stability is restored within approximately 27s and 40s for the respective cases. Resource overhead is minimal, with CPU and memory usage remaining below 7.5% and 2%, respectively. Experiment automation and reproducibility are ensured through Kiso. These findings indicate that role-based programming models complement traditional workflows and that consensus-driven coordination can effectively decentralize decision-making in swarm environments. This approach represents a step toward enabling resilient, decentralized power systems.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1724679</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1724679</link>
        <title><![CDATA[Deployment of transatlantic computational testbeds via the infrastructure manager]]></title>
        <pubdate>2026-02-17T00:00:00Z</pubdate>
        <category>Brief Research Report</category>
        <author>Germán Moltó</author><author>Miguel Caballer</author><author>Estíbaliz Parcero</author><author>Vicente Rodríguez</author>
        <description><![CDATA[Transatlantic scientific collaborations require computational testbeds that can be provisioned on demand and reconfigured rapidly while spanning institutions in different regulatory and operational domains. During the DISCOVER-US exchange program, we integrated the Infrastructure Manager (IM), a TOSCA-based orchestrator for the computing continuum, with the Chameleon cloud infrastructure. The workflow combined federated identity management, delegated project administration, and an IM plugin that targets Chameleon’s OpenStack endpoints through application credentials. We validated the approach by deploying single virtual machines, a production-ready Galaxy environment, distributed OSCAR-based serverless clusters that offload an AI-based fish detection pipeline, a workflow for flood impact modeling, and a hybrid SLURM cluster. Transatlantic computational testbeds included dynamically provisioned computational resources from EGI Federated Cloud and Chameleon. The study also documents operational constraints encountered with lease automation, bare-metal introspection, and the exposure of Kubernetes services across wide-area networks. The resulting blueprint demonstrates a reproducible path to deploy secure, elastic, and scientifically useful transatlantic computational testbeds.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1808241</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1808241</link>
        <title><![CDATA[Retraction: Toward a thermodynamic theory of evolution: a theoretical perspective on information entropy reduction and the emergence of complexity]]></title>
        <pubdate>2026-02-16T00:00:00Z</pubdate>
        <category>Retraction</category>
        
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1794474</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2026.1794474</link>
        <title><![CDATA[Editorial: Game theory and evolutionary dynamics: unraveling complex systems]]></title>
        <pubdate>2026-02-13T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Chengyi Tu</author><author>Hongzhong Deng</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1672525</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1672525</link>
        <title><![CDATA[On the evolutionary dynamics of complexity and consciousness]]></title>
        <pubdate>2026-01-06T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Shimon Edelman</author>
        <description><![CDATA[The perennial debate about the possible directionality of evolution, as indicated by the apparent increase in the complexity of living systems over time, has recently witnessed renewed arguments in favor of the growth of complexity being “entropic,” that is, consistent with the growth of entropy as it is construed in thermodynamics. Here, I offer a brief review of formal treatments of complexity and of evolutionary mechanisms that are capable of causing it to increase. I then propose that both the evolutionary emergence and the individual learning of basic phenomenal awareness, a type of consciousness, are characterized by the same time-asymmetrical dynamics. Like life itself, biological consciousness arguably evolves towards greater complexity, and for the same reasons.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1636222</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fcpxs.2025.1636222</link>
        <title><![CDATA[Organizational regularities in recurrent neural networks]]></title>
        <pubdate>2026-01-05T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Claus Metzner</author><author>Achim Schilling</author><author>Andreas Maier</author><author>Patrick Krauss</author>
        <description><![CDATA[Previous work has shown that the dynamical regime of Recurrent Neural Networks (RNNs)—ranging from oscillatory to chaotic and fixed point behavior—can be controlled by the global distribution of weights in connection matrices with statistically independent elements. However, it remains unclear how network dynamics respond to organizational regularities in the weight matrix, as often observed in biological neural networks. Here, we investigate three such regularities: (1) monopolar output weights per neuron, in accordance with Dale’s principle, (2) reciprocal symmetry between neuron pairs, as in Hopfield networks, and (3) modular structure, where strongly connected blocks are embedded in a background of weaker connectivity. These regularities are studied independently, but as functions of the RNN’s general connection strength and its excitatory/inhibitory bias. For this purpose, we construct weight matrices in which the strength of each regularity can be continuously tuned via control parameters, and analyze how key dynamical signatures of the RNN evolve as a function of these parameters. Moreover, using the RNN for actual information processing in a reservoir computing framework, we study how each regularity affects performance. We find that Dale monopolarity and modularity significantly enhance task accuracy, while Hopfield reciprocity tends to reduce it by promoting early saturation, limiting reservoir flexibility.]]></description>
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