EMERGE’s findings will be communicated at scientific conferences and published in open-access journals. Find below the current list of publications.
Access all publication on the project's Zenodo community clicking here.
Direct Communication or Stigmergy? Selecting Communication Mechanisms for Robot Swarms via Automatic Modular Design
In this paper, we show that automatic modular design (AutoMoDe) can also select between direct communication and stigmergy within a single design process.
David Garzón Ramos, Juan B. Medina, Sabine Hauert, Mauro Birattari (2025). Proceedings of the ALIFE 2025: Ciphers of Life: Proceedings of the Artificial Life Conference 2025. Kyoto, Japan. (pp. 87). DOI: 10.1162/ISAL.a.915
Direct Feedback Alignment for Recurrent Neural Networks
This work adapts Direct Feedback Alignment (DFA) for both “vanilla” and gated recurrent networks.
Folchini, S., Cossu, A., Ceni, A., Lomonaco, V., Bacciu, D., Gallicchio, C. (2026). In High Performance Computing. ISC High Performance 2025. Lecture Notes in Computer Science, vol 16091. DOI: 10.1007/978-3-032-07612-0_9
Distributed Spatial Awareness for Robot Swarms
This paper uses local observations by robots of each other and Gaussian Belief Propagation message passing combined with continuous swarm movement to build a global and distributed swarm-centric frame of reference.
Jones, S., Hauert, S. (2026). In Distributed Autonomous Robotic Systems. DARS 2024. Springer Proceedings in Advanced Robotics, vol 34. DOI: 10.1007/978-3-032-04584-3_36
Diversifying Non-dissipative Reservoir Computing Dynamics
In this paper, the authors propose alternative formulations of the reservoirs for EuSNs, aiming at improving the diversity of the resulting dynamics.
Gallicchio, C. (2023). In Artificial Neural Networks and Machine Learning – ICANN 2023. ICANN 2023. Lecture Notes in Computer Science, vol 14261. Springer, Cham. doi: 10.1007/978-3-031-44198-1_15
Drifting explanations in continual learning
This paper studies the behavior of different explanation methods in CL and propose CLEX (ContinuaL EXplanations), an evaluation protocol to robustly assess the change of explanations in Class-Incremental scenarios, where forgetting is pronounced.
Andrea Cossu, Francesco Spinnato, Riccardo Guidotti, Davide Bacciu, Neurocomputing, 597, 2024, 127960, doi: 10.1016/j.neucom.2024.127960.
Edge of Stability Echo State Network
This paper introduces a new ESN architecture called the Edge of Stability (ESN). The introduced model is based on defining the reservoir layer as a convex combination of a nonlinear reservoir (as in the standard ESN), and a linear reservoir that implements an orthogonal transformation.
A. Ceni and C. Gallicchio, in IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2024.3400045.
Embedded deep reservoir computing for modelling complex industrial systems
This work proposes the use of Deep Echo State Networks to model an industrial system and evaluate its performance in real-time industrial applications when running on embedded devices.
Ramón Rodríguez-Ossorio J, Gallicchio C, Morán A, Díaz I, Fuertes JJ, Domínguez M. Integrated Computer-Aided Engineering. 2025;0(0). doi:10.1177/10692509251376129
Embracing Diversity: A Multi-Perspective Approach with Soft Labels
This paper presents a Multi-Perspective framework for stance detection that explicitly incorporates annotation diversity by using soft labels derived from both human and large language model (LLM) annotations.
Benedetta Muscato, Praveen Bushipaka, Gizem Gezici, Lucia Passaro, Fosca Giannotti, Tommaso Cucinotta, Proceedings of HHAI 2025, pp. 370 - 384. DOI: 10.3233/FAIA250654
EMERGE - Emergent Awareness from Minimal Collectives
This paper introduces the concept of collaborative awareness as a means to enhance interoperability, resilience and self regulation in synthetic agent collectives.
Bacciu, D. et al. (2024). In European Robotics Forum 2024. ERF 2024. Springer Proceedings in Advanced Robotics, vol 32. Springer, Cham. doi: 10.1007/978-3-031-76424-0_16
Enhancing Echo State Networks with Gradient-based Explainability Methods
This work assesses whether a weighted average of hidden states can enhance the Echo State Network performance.
Francesco Spinnato, Andrea Cossu, Riccardo Guidotti, Andrea Ceni, Claudio Gallicchio, and Davide Bacciu, SANN 2024 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges (Belgium) and online event, 9-11 October 2024.
ESN with Delayed Inputs to Model Industrial Processes
This work introduces a Delayed Input Echo State Network to better capture the time-dependent relationships in process modeling.
Rodríguez-Ossorio, J.R., Morán, A., Fuertes, J.J., Gallicchio, C., Roca, L., Domínguez, M. (2025). Engineering Applications of Neural Networks. EANN 2025. Communications in Computer and Information Science, vol 2581. DOI: 10.1007/978-3-031-96196-0_11
Euler State Networks: Non-dissipative Reservoir Computing
Inspired by the numerical solution of ordinary differential equations, this paper proposes a novel Reservoir Computing (RC) model, called the Euler State Network (EuSN).
Claudio Gallicchio, Neurocomputing, 579, 127411, 2024, doi: 10.1016/j.neucom.2024.127411.
Evaluating Online Moderation via LLM-Powered Counterfactual Simulations
This work designs a LLM-powered simulator of Online Social Networks conversations enabling a parallel, counterfactual simulation where toxic behavior is influenced by moderation interventions, keeping all else equal.
Fidone, G., Passaro, L., & Guidotti, R. (2026). Proceedings of the AAAI Conference on Artificial Intelligence, 40(45), 38451-38459. DOI: 10.1609/aaai.v40i45.41186
Evolving and generalising morphologies for locomoting micro-scale robotic agents
This paper explores how the morphology of a multi-cellular micro-robotic agent can be optimised for reliable locomotion using artificial evolution in a stochastic environment.
Uppington, M., Gobbo, P., Hauert, S., & Hauser, H. Journal of Micro and Bio Robotics, 1-11, 2023. DOI: 10.1007/s12213-023-00155-8
Evolving Dynamic Fault Mitigation Strategies in a Robot Swarm for Collective Transportation
This paper presents a novel approach to learning dynamic fault mitigation via neuroevolution, where mitigation actions are implemented by both faulty and non-faulty robots in a collective transport scenario.
Lee, S., Hauert, S. (2025). Lecture Notes in Computer Science, vol 15612.
ExpliCa: Evaluating Explicit Causal Reasoning in Large Language Models
This paper introduces ExpliCa, a new dataset for evaluating LLMs in explicit causal reasoning.
Martina Miliani, Serena Auriemma, Alessandro Bondielli, Emmanuele Chersoni, Lucia Passaro, Irene Sucameli, and Alessandro Lenci. 2025. In Findings of the Association for Computational Linguistics: ACL 2025, pages 17335–17355, Vienna, Austria. DOI: 10.18653/v1/2025.findings-acl.891
Fast: Similarity-Based Knowledge Transfer for Efficient Policy Learning
This work challenges the key issues in Transfer Learning to improve knowledge transfer, agents performance across tasks and reduce computational costs.
A. Capurso, E. Piccoli and D. Bacciu, 2025 IEEE Conference on Games (CoG), Lisbon, Portugal, 2025, pp. 1-8, doi: 10.1109/CoG64752.2025.11114355.
FinFix: A Soft Gripper With Contact-Reactive Reflex for High-Speed Pick and Place of Fragile Objects
This paper investigates using soft technology to solve the challenge of industrial automation calling for precise tasks with cycle times reduced to the minimum while maintaining accelerations low to keep interaction forces under a certain threshold to avoid damage when handling delicate products.
W. Heeringa, C. D. Santina and G. Smit, 2023 IEEE International Conference on Soft Robotics (RoboSoft), Singapore, Singapore, 2023, pp. 1-7, DOI: 10.1109/RoboSoft55895.2023.10122107.
