Modelling competition for space: Emergent inefficiency and inequality due to spatial self-organization among a group of crowd-avoiding agents
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866912969749692416 |
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| author | Mathew, Ann Mary Sasidevan, V |
| author_facet | Mathew, Ann Mary Sasidevan, V |
| contents | Competition for a limited resource is the hallmark of many complex systems, and often, that resource turns out to be the physical space itself. In this work, we study a novel model designed to elucidate the dynamics and emergence in complex adaptive systems in which agents compete for some spatially spread resource. Specifically, in the model, the dynamics result from the agents trying to position themselves in the quest to avoid physical crowding experienced locally. We characterize in detail the dependence of the emergent behavior of the model on the population density of the system and the individual-level agent traits such as the extent of space an agent considers as her neighborhood, the limit of occupation density one tolerates within that neighborhood, and the information accessibility of the agents about neighborhood occupancy. We show that inefficiency in utilizing physical space shows transition at a specific density and peaks at another distinct density. Furthermore, we demonstrate that the variation of inefficiency relative to the information accessible to the agents exhibits contrasting behavior above and below this second density. We also look into the inequality of resource sharing in the model and show that although inefficiency can be a non-monotonic function of information depending upon the parameters of the model, inequality, in general, decreases with information. Our study sheds light on the role of competition, spatial constraints, and agent traits within complex adaptive systems, offering insights into their emergent behaviors. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_21537 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Modelling competition for space: Emergent inefficiency and inequality due to spatial self-organization among a group of crowd-avoiding agents Mathew, Ann Mary Sasidevan, V Physics and Society Statistical Mechanics Competition for a limited resource is the hallmark of many complex systems, and often, that resource turns out to be the physical space itself. In this work, we study a novel model designed to elucidate the dynamics and emergence in complex adaptive systems in which agents compete for some spatially spread resource. Specifically, in the model, the dynamics result from the agents trying to position themselves in the quest to avoid physical crowding experienced locally. We characterize in detail the dependence of the emergent behavior of the model on the population density of the system and the individual-level agent traits such as the extent of space an agent considers as her neighborhood, the limit of occupation density one tolerates within that neighborhood, and the information accessibility of the agents about neighborhood occupancy. We show that inefficiency in utilizing physical space shows transition at a specific density and peaks at another distinct density. Furthermore, we demonstrate that the variation of inefficiency relative to the information accessible to the agents exhibits contrasting behavior above and below this second density. We also look into the inequality of resource sharing in the model and show that although inefficiency can be a non-monotonic function of information depending upon the parameters of the model, inequality, in general, decreases with information. Our study sheds light on the role of competition, spatial constraints, and agent traits within complex adaptive systems, offering insights into their emergent behaviors. |
| title | Modelling competition for space: Emergent inefficiency and inequality due to spatial self-organization among a group of crowd-avoiding agents |
| topic | Physics and Society Statistical Mechanics |
| url | https://arxiv.org/abs/2407.21537 |