Search in a maze-like environment with ant algorithms: Complexity, size and energy study

Zainab Husain, Dymitr Ruta, Fabrice Saffre, Yousof Al-Hammadi, Abdel F. Isakovic

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


We demonstrate the applicability of inverted Ant Algorithms (iAA) for target search in a complex unknown indoor environment with obstructed topology, simulated by a maze. The colony of autonomous ants lay repellent pheromones according to the novel local interaction policy designed to speed up exploration of the unknown maze instead of reinforcing presence in already visited areas. The role of a target-collocated beacon emitting a rescue signal within the maze is evaluated in terms of its utility to guide the search. Different models of iAA were developed, with beacon initialization (iAA-B), and with increased sensing ranges (iAA-R with a 2-step far-sightedness) to quantify the most effective one. Initial results with mazes of various sizes and complexity demonstrate our models are capable of localizing the target faster and more efficiently than other open searches reported in the literature, including those that utilized both AA and local path planning. The presented models can be implemented with self-organizing wireless sensor networks carried by autonomous drones or vehicles and can offer life-saving services of localizing victims of natural disasters or during major infrastructure failures.

Original languageBritish English
Title of host publicationSwarm Intelligence - 11th International Conference, ANTS 2018, Proceedings
EditorsChristian Blum, Andreagiovanni Reina, Marco Dorigo, Mauro Birattari, Anders L. Christensen, Vito Trianni
PublisherSpringer Verlag
Number of pages13
ISBN (Print)9783030005320
StatePublished - 2018
Event11th International Conference on Swarm Intelligence, ANTS 2018 - Rome, Italy
Duration: 29 Oct 201831 Oct 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11172 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th International Conference on Swarm Intelligence, ANTS 2018


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