An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call ant system (AS). We propose it as a viable new approach to stochastic combinatorial optimization. The main characteristics of this model are positive feedback, distributed computation, and the use of a constructive greedy heuristic. Positive feedback accounts for rapid discovery of good solutions, distributed computation avoids premature convergence, and the greedy heuristic helps find acceptable solutions in the early stages of the search process. We apply the proposed methodology to the classical traveling salesman problem (TSP), and report simulation results. We also discuss parameter selection and the early setups of the model, and compare it with tabu search and simulated annealing using TSP. To demonstrate the robustness of the approach, we show how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling. Finally we discuss the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.

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Ant system: optimization by a colony of cooperating agents

This paper introduces the ant colony system (ACS), a distributed algorithm that is applied to the traveling salesman problem (TSP). In the ACS, a set of cooperating agents called ants cooperate to find good solutions to TSPs. Ants cooperate using an indirect form of communication mediated by a pheromone they deposit on the edges of the TSP graph while building solutions. We study the ACS by running experiments to understand its operation. The results show that the ACS outperforms other nature-inspired algorithms such as simulated annealing and evolutionary computation, and we conclude comparing ACS-3-opt, a version of the ACS augmented with a local search procedure, to some of the best performing algorithms for symmetric and asymmetric TSPs.

http://www-igm.univ-mlv.fr/~lombardy/ens/JavaTTT0708/fourmis.pdf

Ant colony system: a cooperative learning approach to the traveling salesman problem

From the Publisher:
The old opposition of matter versus mind stubbornly persists in the way we study mind and brain. In treating cognition as problem solving, Andy Clark suggests, we may often abstract too far from the very body and world in which our brains evolved to guide us. Whereas the mental has been treated as a realm that is distinct from the body and the world, Clark forcefully attests that a key to understanding brains is to see them as controllers of embodied activity. From this paradigm shift he advances the construction of a cognitive science of the embodied mind.

/pdf/being-there-putting-brain-body-and-world-together-again-31tt4y51ml.pdf

Being There: Putting Brain, Body, and World Together Again

https://www.cs.cmu.edu/~illah/PAPERS/socialroboticssurvey.pdf

A survey of socially interactive robots

Ants colonies exhibit very interesting behaviours: even if a single ant only has simple capabilities, the behaviour of a whole ant colony is highly structured. This is the result of coordinated interactions. But, as communication possibilities among ants are very limited, interactions must be based on very simple flows of information. In this paper we explore the implications that the study of ants behaviour can have on problem solving and optimization. We introduce a distributed problem solving environment and propose its use to search for a solution to the travelling salesman problem.

Distributed Optimization by Ant Colonies

This paper presents a series of experiments where a group of mobile robots gather 81 randomly distributed objects and cluster them into one pile. Coordination of the agents’ movements is achieved through stigmergy. This principle, originally developed for the description of termite building behaviour, allows indirect communication between agents through sensing and modification of the local environment which determines the agents’ behaviour. The efficiency of the work was measured for groups of one to five robots working together. Group size is a critical factor. The mean time to accomplish the task decreases for one, two, and three robots respectively, then increases again for groups of four and five agents, due to an exponential increase in the number of interactions between robots which are time consuming and may eventually result in the destruction of existing clusters. We compare our results with those reported by Deneubourg et al. (1990) where similar clusters are observed in ant colonies, generated by the probabilistic behaviour of workers.

/pdf/fom-local-actions-to-global-tasks-stigmergy-and-collective-2b1prn5v0t.pdf

Fom Local Actions to Global Tasks: Stigmergy and Collective Robotics

Trails and U-turns in the Selection of a Path by the Ant Lasius niger

A series of experiments shows how the andLasius niger uses its trail recruitment system to select between two food sources Simultaneously presented with to 1M sucrose solution it concentrates on one of them When offered a 1M solution together with a 01M solution it selects the richer source, unless the trait to the 01M source had become well-developed before the 1M source was introduced In the same situation, however, the group/mass recruiting antTetramorium caespitum uses its more individual transmission of information to switch to the 1M source A mathematical model describes these processes and its dynamics reflect the experimental results

/pdf/collective-decision-making-through-food-recruitment-1afqojdj4o.pdf

Collective decision making through food recruitment

Some 12,000 ant species are known by now, with colony sizes ranging from a few individuals to 20,000,000 individuals. What constraints does this vast range of colony sizes place on the systems of organisation that they use? Alternatively, how does this range of colony sizes reflect the different systems of organisation used? We shall examine these questions in relation to ant foraging strategy, which as well as being the most visible aspect of their activity illustrates most clearly the roles and limits of communication in their collective behavior. This paper aims to verify a prediction of the following hypothesis (Pasteels et al. 1985; Deneubourg et al. 1986). In theory, the organization of a small insect society can rely on most individuals at any moment \"knowing\", principally by learning, what it must do, where it must go, etc., and the workers’ behavior has a strong determinist component. In a large insect society organization by individual learning is harder to achieve (Deneubourg et al. 1987). The workers’ behavior is necessarily more random and their coordination becomes a major problem. To cope with this, a completely different organisational system is added to that already in place. This supplementary system is based on the complex collective structures, patterns and decisions that spontaneously emerge from simple autocatalytic interactions between numerous individuals and with the environment, mediated by essentially chemical communication (see, e.g., Pasteels et al. 1987; Goss and Deneubourg 1989; Beckers et al. in press; Deneubourg et al, 1989, in press; Goss et al. 1990). The prediction that follows from this hypothesis is that the larger the colony size, the less foraging is individually based and the more

/pdf/colony-size-communication-and-ant-foraging-strategy-23z94y3v6z.pdf

Colony size, communication and ant foraging strategy

Foragers of the ant Lasius nigerexploiting a 1 Msugar source were found to lay 43 %more trail marks than those exploiting a 0.05 or a 0.1 Msource. The trail laying per forager decreased during the course of individual recruitment episodes, and the mean lifetime of the trail pheromone was estimated to be 47 min. A mathematical function describing the probability that a forager chooses one of two paths in relation to the amount of trail pheromone on them closely fitted experimental data. These results were incorporated into a model describing the recruitment dynamics of L. niger.Simulations of this model showed that the observed modulation of trail laying with respect to food source quality is sufficient in itself to account for the systematic selection of the richer source seen in the experiments.

Ralph Beckers

Papers

Fom Local Actions to Global Tasks: Stigmergy and Collective Robotics

Trails and U-turns in the Selection of a Path by the Ant Lasius niger

Collective decision making through food recruitment

Colony size, communication and ant foraging strategy

Modulation of trail laying in the ant Lasius niger (Hymenoptera: Formicidae) and its role in the collective selection of a food source