Titlebook: Artificial Life and Evolutionary Computation; 13th Italian Worksho Stefano Cagnoni,Monica Mordonini,Marco Villani Conference proceedings 20

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書目名稱Artificial Life and Evolutionary Computation影響因子(影響力)




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Evolving Critical Boolean Networksith given characteristics by means of evolutionary techniques. In this work we make a further step towards more biologically plausible models by aiming at evolving networks with a given fraction of active nodes along the attractors, while constraining the evolutionary process to move across critical

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Self-loops Favour Diversification and Asymmetric Transitions Between Attractors in Boolean Network Madopt Boolean networks to model cellular differentiation, where attractors (or set of attractors) in the network landscape epitomise cell types. Since changes in network topology and functions strongly impact attractor landscape characteristics, in this paper we study how self-loops influence divers

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Evolution of Workers’ Behaviour in Dual Labor Marketsing interest in analysing the link between these phenomena..In this paper we study the effect of the use of temporary contracts on workers’ incentives and in particular we focus on effort decisions of temporary workers. We implement an agent-based model where workers interact in the labor market and

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Evolution of Generosity and Its Infrastructure in Self-organizing Cooperative Societiess Dilemma game. Each agent evaluates the action of its opponent with the help of a threshold as cooperative or defective and responds differently to the two cases. The evolutionary mechanism consists in copying the behavior of more successful agents met at random in the society. First, we study vari

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Unveiling Latent Relations in the Photonics Techno-Economic Complex System is to uncover indirect latent relations among agents interacting in a specific techno-economic segment (TES). A methodology, including an “Extract-Transform-Load” (ETL) process preceding the two steps aimed for analysis, is developed to analyse a TES regarding R&D economic processes of the photonic

irritation

Combining Machine Learning and Agent Based Modeling for Gold Price Predictione agent based model allows to simulate the market conditions that produced the financial time series and simulated annealing optimize the parameters for the agent based model. The originality of our approach stays in the combination of financial market simulation with meta-learning of its parameters

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