Desert ants can find their way home even if dropped, proving their ability to navigate with a brain the size of a sesame seed.

How lost “passenger” ants find their way home

Ants can effectively forage on one-way trails, overcoming the disruption of orientation cues and navigating through unidirectional traffic systems.

Ants Can Learn to Forage on One-Way Trails

Ants navigate their nests using scent markings and movements of proximate ants, avoiding getting lost in the maze.

Communication of Ants

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Despite being only a few millimetres long and living in what most humans would perceive as a featureless environment, desert ants ( Cataglyphis fortis ) have no problems finding their way back to the nest having meandered around on a foraging expedition. Ants use path integration

PEDOMETER HELPS ANTS GET HOME

Ants form complex transportation networks, using pheromones and sight to navigate to food sources and return to their nests, with some species absconding in the trails to search for food.

Diversity, distribution and secrets of ant transportation networks

Colony emigration in the ant Aphaenogaster senilis involves a synchronized relocation of workers, with some differences in worker relocation methods.

Dynamics of colony emigration in the ant Aphaenogaster senilis

Ants led by a robotic gantry were significantly more successful at finding their way home, even without a trail laid by the leader.

Robotic communication with ants

The ant colony optimization methodology outperforms other methods in terms of solution quality, evaluation time, and processing time for optimal clustering of N objects into K clusters.

An ant colony approach for clustering

Ant Leptothorax albipennis colony emigrates to the best available new site using a quorum requirement, relying on decentralized interactions of poorly informed insects to achieve adaptive behaviors.

Quorum sensing, recruitment, and collective decision-making during colony emigration by the ant Leptothorax albipennis

The wood ant Formica polyctena Först. has survived in an old nuclear weapons bunker for years, despite low temperatures and scanty food, due to the unique accumulation of workers in a gigantic pitfall.

Living beyond the limits of survival: wood ants trapped in a gigantic pitfall

The Ant Colony Optimization (ACO) algorithm effectively solves various discrete optimization problems by mimicking real ants' shortest-path finding abilities and using pheromone trails for communication.

Ant Colony Optimization

The ant colony search algorithm (ACSA) effectively reduces power loss in distribution networks compared to genetic algorithms and simulated annealing methods.

Distribution network reconfiguration for loss reduction by ant colony search algorithm

The wood ant Formica polyctena Först. successfully escaped an old nuclear weapons bunker by using a ventilation pipe and cannibalism to survive and grow.

Ants trapped for years in an old bunker; survival by cannibalism and eventual escape

Ant colony optimization (ACO) is a successful swarm intelligence technique that uses pheromones to guide other ants towards a favorable path, with numerous successful applications.

Ant colonies can improve their collective performance through experience and memory-like processes, reducing emigration times over successive emigrations.

Improvement in collective performance with experience in ants

Ant colony optimization (ACO) is a successful swarm intelligence technique that uses pheromones to guide other ants towards a favorable path, with applications in various fields.

Ant colony optimization

The ant colony method is a metaheuristic that is inspired by ant behavior, which shows that ants can collectively find optimal solutions for their development and survival, with a biomass similar to that of humans.

The Ant Colony Method

Ant Colony Optimization" is an algorithm that mimics real ant abilities to solve complex problems, demonstrating better performance than other optimization heuristics.

ANT COLONY OPTIMIZATION

Ant colony optimization, inspired by real ant colonies, can effectively solve discrete, continuous, and telecommunications problems, with potential for hybridization with AI and operations research techniques.

Ant colony optimization: Introduction and recent trends

Ant Colony Optimization (ACO) has advanced significantly since its initial proposal, with high-performing variants, a generic framework, and successful applications on various computationally hard problems.

Ant Colony Optimization: Overview and Recent Advances

How do ants find their way back to the colony if they get lost?

These studies suggest ants find their way back to the colony using path integration, scent markings, pheromones, and visual cues.