Stigmergic MASA: A Stigmergy Based Algorithm for Multi-Target Search

Abstract

Abstract-We explore the on-line problem of coverage where multiple agents have to find a target whose position is unknown, and without a prior global information about the environment. In this paper a novel algorithm for multi-target search is described, it is inspired from water vortex dynamics and based on the principle of pheromone-based communication. According to this algorithm, called S-MASA (Stigmergic Multi Ant Search Area), the agents search nearby their base incrementally using turns around their center and around each other, until the target is found, with only a group of simple distributed cooperative Ant like agents, which communicate indirectly via depositing/detecting markers. This work improves the search performance in comparison with random walk and S-random walk (stigmergic random walk) strategies, we show the obtained results using computer simulations.

Energy Expenditure in Multi-Agent Foraging: An Empirical Analysis

“…In Ec-marking algorithm, the paths are not optimal when number of agents is small thus energy consumption is great, with the increase of agent's number the length of paths will be reduced and the energy consumption decreases. Because of the optimal paths provided by S-MASA algorithm [15], EC-SAF gives better results than the Ec-marking one (see Figure 6(a)). Results in obstacle environment are similar to the ones in obstaclefree environment configuration, with additional steps needed to avoid obstacles (see Figure 6(b)).…”

“…It is reduced with 16 sinks, since the path length to food is reduced. ES-CAF provide less energy consumption rather than Ecmarking because of the optimal paths induced by the S-MASA algorithm [15]. Figure 6(c) shows the results comparison between the two algorithms.…”

“…While the total energy increased with the increase in number of ticks, it stops changing and becomes stable when all food is foraged and the search space boundaries are reached. EC-SAF gives better results than the enhanced c-marking one, because of the optimal paths and the quick search provided by S-MASA algorithm [15].…”

“…C-SAF robots are ant-like agents with limited computing and memory capacities. C-SAF provides quick search by using S-MASA algorithm [15] as search strategy, and quick exploitation by recruiting agents. Results are better than the standard reference algorithm and performances are emphasized with cooperation [16].…”

ANT: Agent Stigmergy-Based IoT-Network for Enhanced Tourist Mobility

“…There are a few similar approaches, such as papers [35,36], but their objectives are different from ours. watches, etc.).…”