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Individually Stable Dynamics in Coalition Formation over Graphs
No full textInternational audienceCoalition formation over graphs is a well studied class of games whose players are vertices and feasible coalitions must be connected subgraphs. In this setting, the existence and computation of equilibria, under various notions of stability, has attracted a lot of attention. However, the natural process by which players, starting from any feasible state, strive to reach an equilibrium after a series of unilateral improving deviations, has been less studied. We investigate the convergence of dynamics towards individually stable outcomes under the following perspective: what are the most general classes of preferences and graph topologies guaranteeing convergence? To this aim, on the one hand, we cover a hierarchy of preferences, ranging from the most general to a subcase of additively separable preferences, including individually rational and monotone cases. On the other hand, given that convergence may fail in graphs admitting a cycle even in our most restrictive preference class, we analyze acyclic graph topologies such as trees, paths, and stars.</div
Publish or Perish – do French hospitals disclose their greenhouse gas emissions for vertical differentiation?
No full textInternational audienceFrench legislation requires large and medium-sized hospitals to publicly report their greenhouse gas (GHG) emissions. Yet, many hospitals fail to comply with this regulation, while others report voluntarily. The organizational drivers behind this behavior remain underexplored. This study examines whether hospitals disclose their GHG emissions aspart of a broader strategy to differentiate themselves—similar to how they report patient satisfaction scores to signal quality. We explore whether carbon reporting is used as a vertical differentiation strategy in the French healthcare system. We used a mixed-methods approach. First, we analyzed national administrative data to test whether reporting GHG emissions is associated with reporting patient satisfaction scores. Second, we conducted semi-structured interviews with hospital managers to understand the motivations behind emissions reporting. Quantitatively, we found no significant association between the two types of reporting. Hospitals do not appear to use GHG emissions disclosure and patient satisfaction scores as part of the same signaling strategy. Qualitative findings confirmedthat GHG reporting is primarily driven by internal factors such as executive leadership, process improvement, and organizational values, rather than external differentiation or patient demand. Carbon reporting in French hospitals is not currently used as a differentiation strategy. Stronger regulatory enforcement is needed to ensure compliance. Inaddition, hospitals require support—through methodological guidance, training, and the development of dedicated sustainability roles—to integrate environmental performance into their management systems and contribute meaningfully to healthcare decarbonization
On a Simple Hedonic Game with Graph-Restricted Communication
No full textInternational audienceWe study a hedonic game for which feasible coalitions are prescribed by a graph representing the agents’ social relations. A group of agents can form a feasible coalition if and only if their corresponding vertices can be spanned with a star. This requirement guarantees that agents are connected, close to each other, and one central agent can coordinate the actions of the group. In our game, everyone strives to join the largest feasible coalition. We study the existence and computational complexity of both Nash stable and core stable partitions. Then, we provide tight or asymptotically tight bounds on their efficiency, measured in terms of the price of anarchy and the price of stability, under two natural social functions, namely, the number of agents who are not in a singleton coalition, and the number of coalitions. We also derive refined bounds for games in which the social graph is claw-free. Finally, we investigate the complexity of computing socially optimal partitions, as well as extreme Nash stable ones
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation
No full textThe marginal likelihood, or evidence, plays a central role in Bayesian model selection, yet remains notoriously challenging to compute in likelihood-free settings. While Simulation-Based Inference (SBI) techniques such as Sequential Neural Likelihood Estimation (SNLE) offer powerful tools to approximate posteriors using neural density estimators, they typically do not provide estimates of the evidence. In this technical report presented at BayesComp 2025, we present a simple and general methodology to estimate the marginal likelihood using the output of SNLE
Contact‐ and Water‐Mediated Interactions With an Allelopathic Macroalga Drive Distinct Coral Microbiome and Metabolome
No full textInternational audienceMacroalgal proliferation constitutes a major threat to coral reef resilience. Macroalgae can affect corals by altering their microbiome and metabolome. However, our understanding of the spatial scale of these effects and the influence of environmental factors is limited. We conducted a manipulative field experiment to investigate how interaction types (direct contact and close proximity) with the allelopathic macroalga Dictyota bartayresiana and prevailing water current influence the microbiome and metabolome of the coral Pocillopora acuta and its near‐surface seawater. Coral tissue damage was spatially constrained to the algal contact zone. Direct contact caused significant increases in harmful bacteria at the expense of beneficial ones in side coral fragments. Non‐significant changes were observed within the microbiome of apex fragments, suggesting a resistance of the coral holobiont to colony‐wide microbial colonisation. The coral metabolome responded to both algal contact and proximity. We detected several compounds potentially relevant for oxidative stress mitigation and coral defence. This metabolomic response was similar between apex and side fragments, supportive of a colony‐wide metabolomic response. In the near‐surface coral seawater, only a microbial response to algal contact was detected. We conclude that coral holobionts are capable of colony‐wide metabolomic responses to maintain homeostasis against macroalgal competitors
Physics-Informed Graph Neural Networks for Attack Path Prediction
No full textInternational audienceThe automated identification and evaluation of potential attack paths within infrastructures is a critical aspect of cybersecurity risk assessment. However, existing methods become impractical when applied to complex infrastructures. While machine learning (ML) has proven effective in predicting the exploitation of individual vulnerabilities, its potential for full-path prediction remains largely untapped. This challenge stems from two key obstacles: the lack of adequate datasets for training the models and the dimensionality of the learning problem. To address the first issue, we provide a dataset of 1033 detailed environment graphs and associated attack paths, with the objective of supporting the community in advancing ML-based attack path prediction. To tackle the second, we introduce a novel Physics-Informed Graph Neural Network (PIGNN) architecture for attack path prediction. Our experiments demonstrate its effectiveness, achieving an F1 score of 0.9308 for full-path prediction. We also introduce a self-supervised learning architecture for initial access and impact prediction, achieving F1 scores of 0.9780 and 0.8214, respectively. Our results indicate that the PIGNN effectively captures adversarial patterns in high-dimensional spaces, demonstrating promising generalization potential towards fully automated assessments
When Plans Meet Reality: The tangle of Improvisation and Planning in Crisis Situations
No full textInternational audiencePlanning is crucial in crisis preparedness. Yet well-prepared plans often fail to provide an adequate response due to the unpredictability of crises. Consequently, responses often require improvisation, shaped by contingencies and time constraints. However, research on risks frequently puts planning and improvisation at odds. In this paper, we overcome the seemingly contradictory nature of planning and improvisation and explore how they intertwine in complex technological emergencies. Although organizations develop a wide range of plans, complete prediction of crises is out of reach. That's why we propose that improvisation and planning are complementary to strengthen the resilience of organizations in crisis management. To better understand improvisation, researchers have studied it at individual, group and organizational levels, focusing on its characteristics and dimensions. However, gaps remain in our understanding of the full impact of improvisation, how it interacts with existing crisis plans, and how it unfolds during crises. This article aims to fill these gaps by exploring the influence of improvised actions on the execution of existing crisis management plans