Exploring Dynamic Environments Using Stochastic Search Strategies
This is an incremental literature review for researchers interested in bio-inspired search methods in dynamic environments.
This paper reviews literature on stochastic search strategies for exploring dynamic environments, examining bio-inspired approaches like random walk models with kinesis or taxis, and concludes by discussing optimal foraging strategies as a reliable methodology.
In this paper, we conduct a literature review of laws of motion based on stochastic search strategies which are mainly focused on exploring highly dynamic environments. In this regard, stochastic search strategies represent an interesting alternative to cope with uncertainty and reduced perceptual capabilities. This study aims to present an introductory overview of research in terms of directional rules and searching methods mainly based on bio-inspired approaches. This study critically examines the role of animal searching behavior applied to random walk models using stochastic rules and kinesis or taxis. The aim of this study is to examine existing techniques and to select relevant work on random walks and analyze their actual contributions. In this regard, we cover a wide range of displacement events with an orientation mechanism given by a reactive behavior or a source-seeking behavior. Finally, we conclude with a discussion concerning the usefulness of using optimal foraging strategies as a reliable methodology.