Distributed House-Hunting in Ant Colonies

We introduce the study of the ant colony house-hunting problem from a distributed computing perspective. When an ant colony's nest becomes unsuitable due to size constraints or damage, the colony must relocate to a new nest. The task of identifying and evaluating the quality of potential new nests is distributed among all ants. The ants must additionally reach consensus on a final nest choice and the full colony must be transported to this single new nest. Our goal is to use tools and techniques from distributed computing theory in order to gain insight into the house-hunting process. We develop a formal model for the house-hunting problem inspired by the behavior of the Temnothorax genus of ants. We then show a \Omega(log n) lower bound on the time for all n ants to agree on one of k candidate nests. We also present two algorithms that solve the house-hunting problem in our model. The first algorithm solves the problem in optimal O(log n) time but exhibits some features not characteristic of natural ant behavior. The second algorithm runs in O(k log n) time and uses an extremely simple and natural rule for each ant to decide on the new nest.Comment: To appear in PODC 201

Ant colony optimization with direct communication for the traveling salesman problem

This article is posted here with permission from IEEE - Copyright @ 2010 IEEEAnts in conventional ant colony optimization (ACO) algorithms use pheromone to communicate. Usually, this indirect communication leads the algorithm to a stagnation behaviour, where the ants follow the same path from early stages. This occurs because high levels of pheromone are developed, which force the ants to follow the same corresponding trails. As a result, the population gets trapped into a local optimum solution which is difficult to escape from it. In this paper, a direct communication (DC) scheme is proposed where ants are able to exchange cities with other ants that belong to their communication range. Experiments show that the DC scheme delays convergence and improves the solution quality of conventional ACO algorithms regarding the traveling salesman problem, since it guides the population towards the global optimum solution. The ACO algorithm with the proposed DC scheme has better performance, especially on large problem instances, even though it increases the computational time in comparison with a conventional ACO algorithm

Collective action in ant control:

Leaf-cutting ants (Atta. cephalotes) represents a serious problem to farmers in many parts of Latin America and accounts of ants eating up a whole cassava plot or destroying one or more fruit trees overnight are not uncommon. Ants do not respect farm boundaries. Therefore, farmers who control anthills on their own fields might still face damage on their crops caused by ants coming from neighboring fields where no control measures are taken. In that sense, crop damage caused by leaf-cutting ants constitutes a transboundary natural resource management problem which, in addition to technical interventions, requires organizational interventions to ensure a coordinated effort among farmers to be solved. This paper reports on a research effort initiated by CIAT and implemented jointly between CIAT and farmers in La Laguna - a small community in the Andean Hillsides of Southwestern Colombia. The objective of the research effort was two-fold: i) to identify low cost technical options for ant control, and ii) to analyze and visualize the transboundary nature of the ant control problem and thus identify organizational options to enable collective or coordinated ant control.

White ants, empire and entomo-politics in South Asia

By focussing on the history of white ants in colonial South Asia, this article shows how insects were ubiquitous and fundamental to the shaping of British colonial power. British rule in India was vulnerable to white ants because these insects consumed paper and wood, the key material foundations of the colonial state. The white ant problem also made the colonial state more resilient and intrusive. The sphere of strict governmental intervention was extended to include both animate and inanimate nonhumans, while these insects were invoked as symbols to characterise colonised landscapes, peoples and cultures. Nonetheless, encounters with white ants were not entirely within the control of the colonial state. Despite effective state intervention, white ants didn’t vanish altogether, and remained objects of everyday control till the final decade of colonial rule and after. Meanwhile, colonised and post-colonial South Asians used white ants to articulate their own distinct political agendas. Over time, white ants featured variously as metaphors for Islamic decadence, British colonial exploitation, communism, democratic socialism and more recently, the Indian National Congress. This article argues that co-constitutive encounters between the worlds of insects and politics have been an intrinsic feature of British colonialism and its legacies in South Asia

Ants: Mobile Finite State Machines

Consider the Ants Nearby Treasure Search (ANTS) problem introduced by Feinerman, Korman, Lotker, and Sereni (PODC 2012), where $n$ mobile agents, initially placed at the origin of an infinite grid, collaboratively search for an adversarially hidden treasure. In this paper, the model of Feinerman et al. is adapted such that the agents are controlled by a (randomized) finite state machine: they possess a constant-size memory and are able to communicate with each other through constant-size messages. Despite the restriction to constant-size memory, we show that their collaborative performance remains the same by presenting a distributed algorithm that matches a lower bound established by Feinerman et al. on the run-time of any ANTS algorithm

Characteristics of exotic ants in North America

The worldwide transport of species beyond their native range is an increasing problem, e.g. for global biodiversity. Many introduced species are able to establish in new environments and some even become invasive. However, we do not know which traits enable them to survive and reproduce in new environments. This study aims to identify the characteristics of exotic ants, and to quantitatively test previously postulated but insufficiently tested assumptions. We collected data on nine traits of 93 exotic ant species (42 of them being invasive) and 323 native ant species in North America. The dataset includes 2536 entries from over 300 different sources; data on worker head width were mostly measured ourselves. We analyzed the data with three complementary analyses: univariate and multivariate analyses of the raw data, and multivariate analyses of phylogenetically independent contrasts. These analyses revealed significant differences between the traits of native and exotic ant species. In the multivariate analyses, only one trait was consistently included in the best models, estimated with AICc values: colony size. Thus, of the nine investigated traits, the most important characteristic of exotic ants as compared to native ants appears to be their large colony size. Other traits are also important, however, indicating that native and exotic ants differ by a suite of traits

PB1629-Managing Structure-Invading Ants

As a group, ants are the most difficult household pests to control. In a recent survey, pest control technicians indicated they had more call-backs due to ants than any other insect. Too often our first response to a pest problem is to reach for a can of pesticide. When managing ants, this can lead to disaster. In some cases, such as with Pharaoh ants, spraying ant trails only makes the problem worse. So, learn to identify pest ants, understand their biology and management options and you will be more successful combating them

Aphids, Ants and Ladybirds: a mathematical model predicting their population dynamics

The interaction between aphids, ants and ladybirds has been investigated from an ecological point of view since many decades, while there are no attempts to describe it from a mathematical point of view. This paper introduces a new mathematical model to describe the within-season population dynamics in an ecological patch of a system composed by aphids, ants and ladybirds, through a set of four differential equations. The proposed model is based on the Kindlmann and Dixon set of differential equations, focused on the prediction of the aphids-ladybirds population densities, that share a prey-predator relationship. The population of ants, in mutualistic relationship with aphids and in interspecific competition with ladybirds, is described according to the Holland and De Angelis mathematical model, in which the authors faced the problem of mutualistic interactions in general terms. The set of differential equations proposed here is discretized by means the Nonstandard Finite Difference scheme, successfully applied by Gabbriellini to the mutualistic model. The constructed finite-difference scheme is positivity-preserving and characterized by four nonhyperbolic steady-states, as highlighted by the phase-space and time-series analyses. Particular attention is dedicated to the steady-state most interesting from an ecological point of view, whose asymptotic stability is demonstrated via the Centre Manifold Theory. The model allows to numerically confirm that mutualistic relationship effectively influences the population dynamic, by increasing the peaks of the aphids and ants population densities. Nonetheless, it is showed that the asymptotical populations of aphids and ladybirds collapse for any initial condition, unlike that of ants that, after the peak, settle on a constant asymptotic value

Teamwork in genetic programming

This thesis attempts to solve food collection problems using genetic programming. The genetic program will evolve programs that mimic the way ants can collect food and bring it back to a nest. There are two special factors in this genetic program that make the ants work together in order to solve the problem, as opposed to each ant acting on its own. First, there will be a stream in the environment that the ants must cross to get to the food. Although all ants have the same program, some must move into the water and die, building a bridge for the other ants to cross. The surviving ants must realize that a bridge has already been built that they can use, instead of killing themselves by building another bridge. Second, the food will be too heavy for one ant to lift alone. The ants must find the food, and call to other ants for help. If all of the ants are at food waiting for help, some, but not all, of the ants must realize that they are in a deadlock situation, and leave their food to help other ants. Both of these problems require the ants to use teamwork to solve the problem. The ants must realize what other ants are doing, without direct communication or a state machine within the ants