Large deviation principle for a stochastic process with random reinforced relocations
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT(2023)
摘要
Stochastic processes with random reinforced relocations have been introduced in a series of papers by Boyer and co-authors (Boyer and Solis Salas 2014, Boyer and Pineda 2016, Boyer, Evans and Majumdar 2017) to model animal foraging behaviour. Such a process evolves as a Markov process, except at random relocation times, when it chooses a time at random in its whole past according to some 'memory kernel', and jumps to its value at that random time. We prove a quenched large deviation principle for the value of the process at large times. The difficulty in proving this result comes from the fact that the process is not Markovian due to relocations. Furthermore, the random inter-relocation times act as a random environment.
更多查看译文
关键词
random walk with random relocations,reinforcement,memory,large deviations,quenched
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要