Abstract
Human mobility always had a great influence on the spreading of cultural, social and technological ideas. Developing realistic models that allow for a better understanding, prediction and control of such coupled processes has gained a lot of attention in recent years. However, the modeling of spreading processes that happened in ancient times faces the additional challenge that available knowledge and data is often limited and sparse. In this paper, we present a new agent-based model for the spreading of innovations in the ancient world that is governed by human movements. Our model considers the diffusion of innovations on a spatial network that is changing in time, as the agents are changing their positions. Additionally, we propose a novel stochastic simulation approach to produce spatio-temporal realizations of the spreading process that are instructive for studying its dynamical properties and exploring how different influences affect its speed and spatial evolution.
Highlights
Modeling human mobility behavior is a topic of great relevance, since such models can be used for analyzing and understanding many real-world processes, like migration and traffic flows [1,2,3,4], as well as processes depending on human mobility and interaction, such as epidemic spreading [5, 6] and the propagation of information and innovations [7,8,9,10]
2.4 Modeling the spreading of innovations Given the positional movements of agents in the suitability landscape, we can construct a spatial network between agents that is changing in time, i.e. a time-evolving network [39]
5 Conclusions and future outlook In this paper we presented a general framework for modeling the spreading of an innovation among human individuals in prehistoric times
Summary
Modeling human mobility behavior is a topic of great relevance, since such models can be used for analyzing and understanding many real-world processes, like migration and traffic flows [1,2,3,4], as well as processes depending on human mobility and interaction, such as epidemic spreading [5, 6] and the propagation of information and innovations [7,8,9,10]. Its movement in space is independent of the innovation states of the other agents Based on these assumptions we formulate a model for the spatial migration of agents in Sect. 2.4 Modeling the spreading of innovations Given the positional movements of agents in the suitability landscape, we can construct a spatial network between agents that is changing in time, i.e. a time-evolving network [39]. 2.5 Joint model: movements of the agents and spreading of the innovation We combine the two dynamics, the spreading process and the diffusion process, into one equation that describes the complete process Y (t) = (I(t), X(t)) To this end we define the function f Y (t) = 0, –∇(V + U) X(t) and a Brownian motion. In order to circumvent these problems, we will present our new event-based simulation algorithm, which allows for adaption events to happen continuously in time
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