Mean Field Equilibria for Resource Competition in Spatial Settings
Mean Field Equilibria for Resource Competition in Spatial Settings
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DOI：
10.1287/stsy.2018.0018
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发表时间：
2017-07
期刊：
影响因子：
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通讯作者：
Pu Yang;Krishnamurthy Iyer;P. Frazier
中科院分区：
文献类型：
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作者：
Pu Yang;Krishnamurthy Iyer;P. Frazier
我们研究了在众包交通服务、在线社区和传统的基于位置的经济活动中，游牧代理之间对时变和特定地点资源的竞争模型。该模型由一组智能体和一个被赋予动态随机资源过程的单个位置组成。每个智能体周期性地获得由该位置的资源水平和其他智能体数量决定的奖励，并必须决定是留在该位置还是移动。移动时，智能体到达一个不同的位置，其动态与原始位置独立且相同。利用平均场均衡的方法，研究了智能体的均衡行为与随机资源过程的动态关系以及同址智能体之间竞争的性质。我们展示了一个均衡的存在，其中每个代理仅根据其当前位置的资源水平和其他代理的数量来决定是否切换位置。我们还表明，当一个主体的收益随着其所在位置的其他主体数量的减少而减少时，均衡策略服从一个简单的阈值结构。我们展示了如何利用这种结构来数值计算均衡，并使用这些数值技术来研究系统结构如何影响agent探索其领域以发现和有效利用资源丰富区域的集体能力。
We study a model of competition among nomadic agents for time-varying and location-specific resources, arising in crowd-sourced transportation services, online communities, and traditional location-based economic activity. This model comprises a group of agents and a single location endowed with a dynamic stochastic resource process. Periodically, each agent derives a reward determined by the location's resource level and the number of other agents there, and has to decide whether to stay at the location or move. Upon moving, the agent arrives at a different location whose dynamics are independent and identical to the original location. Using the methodology of mean field equilibrium, we study the equilibrium behavior of the agents as a function of the dynamics of the stochastic resource process and the nature of the competition among co-located agents. We show that an equilibrium exists, where each agent decides whether to switch locations based only on their current location's resource level and the number of other agents there. We additionally show that when an agent's payoff is decreasing in the number of other agents at her location, equilibrium strategies obey a simple threshold structure. We show how to exploit this structure to compute equilibria numerically, and use these numerical techniques to study how system structure affects the agents' collective ability to explore their domain to find and effectively utilize resource-rich areas.