Add to ORKGBy periodically returning a search process to a known or random state, random resetting possesses the potential to unveil new trajectories, sidestep potential obstacles, and consequently enhance the efficiency of locating desired targets. In this chapter, we highlight the pivotal theoretical contributions that have enriched our understanding of random resetting within an abundance of stochastic processes, ranging from standard diffusion to its fractional counterpart. We also touch upon the general criteria required for resetting to improve the search process, particularly when distribution describing the time needed to reach the target is broader compared to a normal one. Building on this foundation, we delve into real-world applications wh...
This article presents the long-term behaviour analysis of Stochastic Diffusion Search (SDS), a distr...
Local search (LS) and multi-agent-based search (ERA [1]) are stochastic and incomplete procedures fo...
In this article we study stochastic multistart methods for global optimization, which combine local ...
Recent theoretical developments had laid down the proper mathematical means to understand how the st...
We consider a stochastic search model with resetting for an unknown stationary target $a\in\mathbb{R...
Recent theoretical developments had laid down the proper mathematical means to understand how the st...
Stochastic resetting, a diffusive process whose amplitude is reset to the origin at random times, is...
AbstractThere is a developing theory of growing power which, at its current stage of development (in...
AbstractAn open problem in the field of random searches relates to optimizing the search efficiency ...
It is often necessary, in scientific or everyday life problems, to find a randomly hidden target. Wh...
We apply the theory of random walks to quantitatively describe the general problem of how to search ...
This paper studies how different search protocols affect social welfare in a search market. There is...
A lively debate exists on the inherent stochasticity involved in many animal search displacements an...
PACS. 87.23.-n – Ecology and evolution. PACS. 05.40.-a – Fluctuation phenomena, random processes, no...
The spectral theory of random walks on networks of arbitrary topology can be readily extended to stu...
This article presents the long-term behaviour analysis of Stochastic Diffusion Search (SDS), a distr...
Local search (LS) and multi-agent-based search (ERA [1]) are stochastic and incomplete procedures fo...
In this article we study stochastic multistart methods for global optimization, which combine local ...
Recent theoretical developments had laid down the proper mathematical means to understand how the st...
We consider a stochastic search model with resetting for an unknown stationary target $a\in\mathbb{R...
Recent theoretical developments had laid down the proper mathematical means to understand how the st...
Stochastic resetting, a diffusive process whose amplitude is reset to the origin at random times, is...
AbstractThere is a developing theory of growing power which, at its current stage of development (in...
AbstractAn open problem in the field of random searches relates to optimizing the search efficiency ...
It is often necessary, in scientific or everyday life problems, to find a randomly hidden target. Wh...
We apply the theory of random walks to quantitatively describe the general problem of how to search ...
This paper studies how different search protocols affect social welfare in a search market. There is...
A lively debate exists on the inherent stochasticity involved in many animal search displacements an...
PACS. 87.23.-n – Ecology and evolution. PACS. 05.40.-a – Fluctuation phenomena, random processes, no...
The spectral theory of random walks on networks of arbitrary topology can be readily extended to stu...
This article presents the long-term behaviour analysis of Stochastic Diffusion Search (SDS), a distr...
Local search (LS) and multi-agent-based search (ERA [1]) are stochastic and incomplete procedures fo...
In this article we study stochastic multistart methods for global optimization, which combine local ...