https://hdl.handle.net/10259/3830 2026-06-21T10:06:45Z 2026-06-21T10:06:45Z Galán Ordax, José Manuel Díaz de la Fuente, Silvia Ahedo García, Virginia Santos Martín, José Ignacio https://hdl.handle.net/10259/11846 2026-06-17T00:05:32Z 2026-03-01T00:00:00Z

Optimizing classroom assignments to minimize epidemiological risk: the sibling rewiring problem Galán Ordax, José Manuel; Díaz de la Fuente, Silvia; Ahedo García, Virginia; Santos Martín, José Ignacio In the context of infectious diseases, the assignment of students to classroom groups can significantly influence infection dynamics within school environments, particularly when sibling relationships introduce latent connections between otherwise unconnected groups. Traditional grouping methods and pandemic-era bubble strategies do not explicitly optimize student network structures or account for equity in exposure. This study introduces the Sibling Rewiring Problem, a novel multi-objective framework for student assignment that aims to maximize network fragmentation, reduce potential contagion pathways and minimize variance in group sizes and epidemiological exposure—thereby promoting fairness. We compared baseline, heuristic, and metaheuristic strategies in realistic school scenarios. A simple heuristic that assigns siblings to the same classroom line when feasible consistently achieves substantial network fragmentation with minimal impact on equity. Simulated Annealing further improved these results, particularly in complex configurations with densely connected sibling networks. Our findings suggest that family-aware classroom assignments can enhance epidemiological resilience while maintaining socially acceptable distributions. This approach provides a practical and scalable framework for integrating public health considerations into educational planning and may inform future decision-making in both emergency and routine contexts

2026-03-01T00:00:00Z Izquierdo, Segismundo S. Izquierdo Millán, Luis Rodrigo https://hdl.handle.net/10259/10864 2025-09-13T00:05:28Z 2025-10-01T00:00:00Z

Statistical inference in games: Stability of pure equilibria Izquierdo, Segismundo S.; Izquierdo Millán, Luis Rodrigo We consider sampling best response decision protocols with statistical inference in population games. Under these protocols, a revising agent observes the actions of k randomly sampled players in a population, estimates from the sample a probability distribution for the state of the population (using some inference method), and chooses a best response to the estimated distribution. We formulate deterministic approximation dynamics for these protocols. If the inference method is unbiased, strict Nash equilibria are rest points, but they may not be stable. We present tests for stability of pure equilibria under these dynamics. Focusing on maximum-likelihood estimation, we can define an index that measures the strength of each strict Nash equilibrium. In tacit coordination or weakest-link games, the stability of equilibria under sampling best response dynamics is consistent with experimental evidence, capturing the effect of strategic uncertainty and its sensitivity to the number of players and to the cost/benefit ratio.

2025-10-01T00:00:00Z Izquierdo, Segismundo S. Izquierdo Millán, Luis Rodrigo Hauert, Christoph https://hdl.handle.net/10259/10460 2025-05-14T00:05:15Z 2025-07-01T00:00:00Z

Positive and negative selective assortment Izquierdo, Segismundo S.; Izquierdo Millán, Luis Rodrigo; Hauert, Christoph In populations subject to evolutionary processes, the assortment of players with different genes or strategies can have a large impact on players’ payoffs and on the expected evolution of each strategy in the population. Here we consider assortment generated by a process of partner choice known as selective assortment. Under selective assortment, players looking for a mate can observe the strategies of a sample of potential mates or co-players, and select one of them to interact with. This selection mechanism can generate positive assortment (preference for players using the same strategy), or negative assortment (preference for players using a different strategy). We study the impact of selective assortment in the evolution and in the equilibria of a population, providing results for different games under different evolutionary dynamics (including the replicator dynamics).

2025-07-01T00:00:00Z Izquierdo Millán, Luis Rodrigo Izquierdo, Segismundo S. Sandholm, William H. https://hdl.handle.net/10259/9649 2024-10-30T01:05:21Z 2024-10-16T00:00:00Z

Agent-Based Evolutionary Game Dynamics: a guide to implement and analyze Agent-Based Models within the framework of Evolutionary Game Theory Izquierdo Millán, Luis Rodrigo; Izquierdo, Segismundo S.; Sandholm, William H. This book is a guide to implement and analyze simple agent-based evolutionary models using NetLogo. All the models we implement are agent-based, i.e. individual agents and their interactions are explicitly represented in the models. To formalise agents’ interactions we use the basic framework of Evolutionary Game Theory. NetLogo is a multi-agent programmable modeling environment used by hundreds of thousands of students, teachers and researchers all around the globe. No coding experience is necessary to fully understand the contents of this book.

2024-10-16T00:00:00Z