Periodic Reporting for period 1 - EvoGamesPlus (Evolutionary games and population dynamics: from theory to applications)
Período documentado: 2021-03-01 hasta 2023-02-28
EVOGAMESPLUS is a project that aims to train 15 high-potential individuals in the state-of-the-art of Evolutionary Game Theory (EGT). Through this project, the ESRs (Early-Stage Researchers) will learn to make EGT models more realistic and apply their knowledge to solve real-world problems using real data.
The primary research objective of EVOGAMESPLUS is to expand Evolutionary Game Theory models and understand their dynamical properties. To achieve this objective, the project has four key scientific objectives. The first objective is to develop game-theoretical models describing interactions in structured populations. The second objective is to expand the EGT field by including dynamical aspects of evolutionary games. The third objective is to develop game-theoretical models to conceptualize cancer and design evolutionary treatments based on in vitro and in vivo data. The fourth objective is to develop more realistic ecological and epidemiological models to predict and prevent epidemics based on epidemiological data.
The primary training objective of EVOGAMESPLUS is to train the ESRs in the development of new Evolutionary Game Theoretic (EGT) models. They will study the dynamical properties of these models and apply them to solve real-world problems using real data, such as patient data and and epidemic data. .
The primary research objective of EVOGAMESPLUS is to expand Evolutionary Game Theory models and understand their dynamical properties. To achieve this objective, the project has four key scientific objectives. The first objective is to develop game-theoretical models describing interactions in structured populations. The second objective is to expand the EGT field by including dynamical aspects of evolutionary games. The third objective is to develop game-theoretical models to conceptualize cancer and design evolutionary treatments based on in vitro and in vivo data. The fourth objective is to develop more realistic ecological and epidemiological models to predict and prevent epidemics based on epidemiological data.
The primary training objective of EVOGAMESPLUS is to train the ESRs in the development of new Evolutionary Game Theoretic (EGT) models. They will study the dynamical properties of these models and apply them to solve real-world problems using real data, such as patient data and and epidemic data. .
WP1 has built on existing structural EGT models, incorporating a number of realistic population features. These include population structure, multi-level selection, multiple and multiplayer interactions, time delays and eco-evolutionary factors.
WP2 has started incorporating techniques from dynamical systems theory into evolutionary game theory, to address questions of stability of equilibria by using numerical and analytical methods.
WP3 has been focusing on games against and for nature, so-called Stackelberg Evolutionary Games, their properties, and application in mathematical oncology, to understand cancer progression and develop novel anti-cancer treatment.
WP4 has been developing more realistic ecological and epidemiological models that can be used to predict and prevent epidemics based on epidemiological data.
Only deliverables D1.1 D2.1 D3.1 and D4.1 thus deliverables related to the first tasks of each content work package, were due in this reporting period. All other content deliverables are due in the future reporting period and, as such, the related research will be reported in the next reporting period.
WP5 has successfully organized ESRs’ trainings, secondments, winter/summer schools, conferences/workshops, and short visits, focusing both on content of the project and soft skills. Additionally, within the training journal clubs organized by WPs and across WPs have been organized, which will lead to review article(s) on the EvoGamesPlus content..
WP6 has successfully managed the network on a daily basis and included formalization of GA and CA, the establishment of the management structure, practical arrangements, and progress monitoring.
WP7 set up the project's communication infrastructure and coordinating related activities
WP8 guarded our obligations to comply with the principles of Ethics which are characteristic for Horizon 2020 program and included in Article 34.1 of the Grant Agreement
WP9 has been focusing on assuring that Evogamesplus results and produced data as open as possible while in line with the ethics requirement. As no data have been utilized so far, due to focus on model development, most outcomes are due in the next reporting period.
WP2 has started incorporating techniques from dynamical systems theory into evolutionary game theory, to address questions of stability of equilibria by using numerical and analytical methods.
WP3 has been focusing on games against and for nature, so-called Stackelberg Evolutionary Games, their properties, and application in mathematical oncology, to understand cancer progression and develop novel anti-cancer treatment.
WP4 has been developing more realistic ecological and epidemiological models that can be used to predict and prevent epidemics based on epidemiological data.
Only deliverables D1.1 D2.1 D3.1 and D4.1 thus deliverables related to the first tasks of each content work package, were due in this reporting period. All other content deliverables are due in the future reporting period and, as such, the related research will be reported in the next reporting period.
WP5 has successfully organized ESRs’ trainings, secondments, winter/summer schools, conferences/workshops, and short visits, focusing both on content of the project and soft skills. Additionally, within the training journal clubs organized by WPs and across WPs have been organized, which will lead to review article(s) on the EvoGamesPlus content..
WP6 has successfully managed the network on a daily basis and included formalization of GA and CA, the establishment of the management structure, practical arrangements, and progress monitoring.
WP7 set up the project's communication infrastructure and coordinating related activities
WP8 guarded our obligations to comply with the principles of Ethics which are characteristic for Horizon 2020 program and included in Article 34.1 of the Grant Agreement
WP9 has been focusing on assuring that Evogamesplus results and produced data as open as possible while in line with the ethics requirement. As no data have been utilized so far, due to focus on model development, most outcomes are due in the next reporting period.
We develop new game theoretic models and increase our understanding of these new models, improving our understanding of not only underlying equilibria, but also the dynamics leading to them. We use these novel game-theoretical tools to design better cancer therapies and measures to control epidemics. The modelling techniqueswe will develop will expand the theory towards the more applicable models.
All WPs of EvoGamesPlus will introduce methodologies expanding the state of the art of their corresponding fields. In WP1, new models expanding evolutionary graph theory will be developed and combined with agent-based modelling. In WP2, dynamical systems theory methods will be brought to evolutionary game theory, expanding the field of EGT to this direction (identifying tipping points, bifurcations, and chaotic behaviour in evolutionary games). In WP3, the novel concept of Stackelberg evolutionary game (SEG) theory will be developed and studied, also in the context of cancer treatment. In WP4, a new generation of ecological models, built upon SIR models, will be developed and validated with big data as an input, using software and machine learning techniques developed by EvoGamesPlus researchers.
All WPs of EvoGamesPlus will introduce methodologies expanding the state of the art of their corresponding fields. In WP1, new models expanding evolutionary graph theory will be developed and combined with agent-based modelling. In WP2, dynamical systems theory methods will be brought to evolutionary game theory, expanding the field of EGT to this direction (identifying tipping points, bifurcations, and chaotic behaviour in evolutionary games). In WP3, the novel concept of Stackelberg evolutionary game (SEG) theory will be developed and studied, also in the context of cancer treatment. In WP4, a new generation of ecological models, built upon SIR models, will be developed and validated with big data as an input, using software and machine learning techniques developed by EvoGamesPlus researchers.