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Marco Dorigo

Université libre de Bruxelles, Faculté des Sciences Appliquées, Faculty Member

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Marco Dorigo received the Laurea, Master of Technology, degree in industrial technologies engineering in 1986, and the PhD degree in electronic engineering in 1992 from Politecnico di Milano, Milan, Italy, and the title of Agrégé de l’Enseignement Supérieur, from Université Libre de Bruxelles (ULB), Brussels, Belgium, in 1995. From 1992 to 1993, he was a Research Fellow with the International Computer Science Institute, Berkeley, CA, USA. In 1993, he was a NATO-CNRFellow, and from 1994 to 1996, a Marie Curie Fellow. Since 1996, he has been a tenured Researcher of the FNRS, the Belgian National Funds for Scientific Research, and the Co-Director of IRIDIA, ULB. He is the inventor of the Ant Colony Optimization metaheuristic. His current research interests include swarm intelligence, swarm robotics, and metaheuristics for discrete optimization.He is Editor-in-Chief of Swarm Intelligence, and an Associate Editoror a member of the Editorial Boards of several journals on computational intelligence and adaptive systems.Prof. Dorigo was a recipient of the Italian Prize for ArtificialIntelligence in 1996, the Marie Curie Excellence Award in 2003, theDr. A. De Leeuw-Damry-Bourlart Award in Applied Sciences in 2005, the Cajastur International Prize for Soft Computing in 2007, an ERC Advanced Grant in 2010, and the IEEE Frank Rosenblatt Award in 2015. He is a fellow of AAAI, ECCAI, and IEEE.

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Papers by Marco Dorigo

Evolving Self-Organizing Behaviors for a Swarm-Bot

by Gianluca Baldassarre, Erol Sahin, Marco Dorigo, and Roderich Gross

Autonomous Robots, 2004

Self-organized discrimination of resources

When selecting a resource to exploit, an insect colony must take into account at least two constr... more When selecting a resource to exploit, an insect colony must take into account at least two constraints: the resource must be abundant enough to sustain the whole group, but not too large to limit exploitation costs, and risks of conflicts with other colonies. Following recent results on cockroaches and ants, we introduce here a behavioral mechanism that satisfies these two constraints. Individuals simply modulate their probability to switch to another resource as a function of the local density of conspecifics locally detected.

Teamwork in self-organized robot colonies

Abstract Swarm robotics draws inspiration from decentralized self-organizing biological systems i... more Abstract Swarm robotics draws inspiration from decentralized self-organizing biological systems in general and from the collective behavior of social insects in particular. In social insect colonies, many tasks are performed by higher order group or team entities, whose task-solving capacities transcend those of the individual participants. In this paper, we investigate the emergence of such higher order entities. We report on an experimental study in which a team of physical robots performs a foraging task.

Reply to Dario Floreano's" Engineering Adaptive Behavior"

Dario Florcano's review of Robot SIItI~ JIrI~ T: All E. uprrinuut ill l3rlraoior EtyL~ irmrrinET ... more

EvoSTIM Papers-Design of Iterated Local Search Algorithms

EvoSTIM Papers-Design of Iterated Local Search Algorithms. Matthijs den Besten, Thomas Stutzle, M... more

Ant-based clustering: a comparative study of its relative performance with respect to-means, average link and 1d-som

Abstract. Ant-based clustering and sorting is a nature-inspired heuristic for general clustering ... more Abstract. Ant-based clustering and sorting is a nature-inspired heuristic for general clustering tasks. It has been applied variously, from problems arising in commerce, to circuit design, to text-mining, all with some promise. However, although early results were broadly encouraging, there has been very limited analytical evaluation of antbased clustering.

Enhancing the cooperative transport of multiple objects

In this paper we present an approach to the cooperative transport of multiple objects in swarm ro... more In this paper we present an approach to the cooperative transport of multiple objects in swarm robotics. The approach is motivated by the observation that the performance of cooperative transport in insect colonies as well as in groups of robots grows in a super linear way with the number of individuals participating in the transport. The transport relies on a cart in which multiple objects are collected and stored before being moved to destination.

TR/IRIDIA/2007-005 March 2007

For any robotic entity to complete a task efficiently, its morphology must be appropriate to the ... more For any robotic entity to complete a task efficiently, its morphology must be appropriate to the task. If the task is well-defined in advance, the morphology of a robotic entity can be pre-specified accordingly. If, however, some of the task parameters are not known in advance, or if the same robotic system is required to solve several different tasks, morphological flexibility may be required. It is easy to imagine, for example, that navigating on uneven terrain and hole-crossing are likely to require different morphologies (see Fig. 1).

Dipartimento Di Elettronica-Politecnico Di Milano

Abstract: A combination of distributed computation, positive feedback and constructive greedy heu... more Abstract: A combination of distributed computation, positive feedback and constructive greedy heuristic is proposed as a new approach to stochastic optimization and problem solving. Positive feedback accounts for rapid discovery of very good solutions, distributed computation avoids premature convergence, and greedy heuristic helps the procedure to find acceptable solutions in the early stages of the search process.

. BIBLIOGRAPHY 306

Abstract Dynamic optimisation problems are problems where the search space does not remain consta... more Abstract Dynamic optimisation problems are problems where the search space does not remain constant over time. Evolutionary algorithms aimed at static optimisation problems often fail to effectively optimise dynamic problems. The main reason for this is that the algorithms converge to a single optimum in the search space, and then lack the necessary diversity to locate new optima once the environment changes.

The Swarm-bot Experience: Strength and Mobility through Physical Cooperation

In this chapter, we study a collective robotic system that is inspired by the behavior of social ... more In this chapter, we study a collective robotic system that is inspired by the behavior of social insects. The system consists of mobile robots that can autonomously perceive and modify their environment. We investigate the problem of controlling a number of these robots in cooperation based tasks that are too difficult for the robots to solve when operating alone.

On the performance of ant-based clustering

Abstract. Ant-based clustering and sorting is a nature-inspired heuristic for general clustering ... more Abstract. Ant-based clustering and sorting is a nature-inspired heuristic for general clustering tasks. It has been applied variously, from problems arising in commerce, to circuit design, to text-mining, all with some promise. However, although early results were broadly encouraging, there has been very limited analytical evaluation of the algorithm. Toward this end, we first propose a scheme that enables unbiased interpretation of the clustering solutions obtained, and then use this to conduct a full evaluation of the algorithm.

Towards a theory of practice in meta-heuristics design

Abstract A number of methodological papers published during the last years, testify that a need f... more Abstract A number of methodological papers published during the last years, testify that a need for a thorough revision of the research methodology is felt by the operations research community—see, for example, Barr et al.(1995), Hooker (1995), and Rardin and Uzsoy (2001). In particular, the performance evaluation of nondeterministic methods, such as the methods known as metaheuristics, require the definition of new experimental protocols.

Special Issue: Ant Algorithms

Colonies of social insects can exhibit an amazing variety of complex behaviors and have captured,... more Colonies of social insects can exhibit an amazing variety of complex behaviors and have captured, since ever, the interest of biologists and entomologists. More recently, computer scientists have found in the study of social insects behavior a source of inspiration for the design and implementation of novel distributed multi-agent algorithms. In particular, the study of ant colonies behavior turned out to be very fruitful, giving raise to a completely novel field of research, now known as ant algorithms.

Frankenstein’s PSO: An Engineered Composite Particle Swarm Optimization Algorithm

Abstract We introduce a high-performing composite particle swarm optimization (PSO) algorithm. In... more Abstract We introduce a high-performing composite particle swarm optimization (PSO) algorithm. In an analogy to the popular character of Mary Shelley's famous novel, we call our algorithm Frankenstein's PSO, as it consists of different algorithmic components drawn from other PSO variants. Frankenstein's PSO constituents were selected after careful evaluation of their impact on speed and reliability.

Incremental robot shaping

We propose a modular architecture for autonomous robots which allows for the implementation of ba... more We propose a modular architecture for autonomous robots which allows for the implementation of basic behavioral modules by both programming and training, and accommodates for an evolutionary development of the interconnections among modules. This architecture can implement highly complex controllers and allows for incremental shaping of the robot behavior.

Local search and metaheuristics for the quadratic assignment problem

The quadratic assignment problem (QAP) is an important problem in theory and practice. It was, wh... more The quadratic assignment problem (QAP) is an important problem in theory and practice. It was, which was introduced by Koopmans and Beckmann in 1957 [28] and is a model for many practical problems like backboard wiring [53], campus and hospital layout [15, 17], typewriter keyboard design [9], scheduling [23] and many others [16, 29] can be formulated as QAPs.

SWARM-BOT: Pattern formation in a swarm of self-assembling mobile robots

Abstract We introduce a new robotic system, called swarm-bot. The system consists of a swarm of m... more Abstract We introduce a new robotic system, called swarm-bot. The system consists of a swarm of mobile robots with the ability to connect to/disconnect from each other to self-assemble into different kinds of structures. First, we describe our vision and the goals of the project. Then we present preliminary results on the formation of patterns obtained from a grid-world simulation of the system.

Open e-puck range & bearing miniaturized board for local communication in swarm robotics

Abstract We have designed and built a new open hardware/software board that lets miniaturized rob... more Abstract We have designed and built a new open hardware/software board that lets miniaturized robots communicate and at the same time obtain the range and bearing of the source of emission. The open E-puck Range & Bearing board improves an existing infrared relative localization/communication software library (libIrcom) developed for the e-puck robot and based on its on-board infrared sensors. The board allows the robots to have an embodied, decentralized and scalable communication system.

An insect-based algorithm for the dynamic task allocation problem

An insect-based algorithm inspired by the division of labor in insect colonies is proposed and ap... more An insect-based algorithm inspired by the division of labor in insect colonies is proposed and applied to the solution of an online scheduling problem. A painting facility is considered for illustrating the problem: Trucks leave an assembly line to get painted in painting booths. The goal is to minimize the makespan, that is, the time needed for painting all given trucks. In this paper we address two issues. First, we propose and analyze four modifications of an insect-based algorithm previously introduced by Cicirello and Smith.

Evolving Self-Organizing Behaviors for a Swarm-Bot

by Gianluca Baldassarre, Erol Sahin, Marco Dorigo, and Roderich Gross

Autonomous Robots, 2004

Self-organized discrimination of resources

When selecting a resource to exploit, an insect colony must take into account at least two constr... more When selecting a resource to exploit, an insect colony must take into account at least two constraints: the resource must be abundant enough to sustain the whole group, but not too large to limit exploitation costs, and risks of conflicts with other colonies. Following recent results on cockroaches and ants, we introduce here a behavioral mechanism that satisfies these two constraints. Individuals simply modulate their probability to switch to another resource as a function of the local density of conspecifics locally detected.

Teamwork in self-organized robot colonies

Abstract Swarm robotics draws inspiration from decentralized self-organizing biological systems i... more Abstract Swarm robotics draws inspiration from decentralized self-organizing biological systems in general and from the collective behavior of social insects in particular. In social insect colonies, many tasks are performed by higher order group or team entities, whose task-solving capacities transcend those of the individual participants. In this paper, we investigate the emergence of such higher order entities. We report on an experimental study in which a team of physical robots performs a foraging task.

Reply to Dario Floreano's" Engineering Adaptive Behavior"

Dario Florcano's review of Robot SIItI~ JIrI~ T: All E. uprrinuut ill l3rlraoior EtyL~ irmrrinET ... more

EvoSTIM Papers-Design of Iterated Local Search Algorithms

EvoSTIM Papers-Design of Iterated Local Search Algorithms. Matthijs den Besten, Thomas Stutzle, M... more

Ant-based clustering: a comparative study of its relative performance with respect to-means, average link and 1d-som

Abstract. Ant-based clustering and sorting is a nature-inspired heuristic for general clustering ... more Abstract. Ant-based clustering and sorting is a nature-inspired heuristic for general clustering tasks. It has been applied variously, from problems arising in commerce, to circuit design, to text-mining, all with some promise. However, although early results were broadly encouraging, there has been very limited analytical evaluation of antbased clustering.

Enhancing the cooperative transport of multiple objects

In this paper we present an approach to the cooperative transport of multiple objects in swarm ro... more In this paper we present an approach to the cooperative transport of multiple objects in swarm robotics. The approach is motivated by the observation that the performance of cooperative transport in insect colonies as well as in groups of robots grows in a super linear way with the number of individuals participating in the transport. The transport relies on a cart in which multiple objects are collected and stored before being moved to destination.

TR/IRIDIA/2007-005 March 2007

For any robotic entity to complete a task efficiently, its morphology must be appropriate to the ... more For any robotic entity to complete a task efficiently, its morphology must be appropriate to the task. If the task is well-defined in advance, the morphology of a robotic entity can be pre-specified accordingly. If, however, some of the task parameters are not known in advance, or if the same robotic system is required to solve several different tasks, morphological flexibility may be required. It is easy to imagine, for example, that navigating on uneven terrain and hole-crossing are likely to require different morphologies (see Fig. 1).

Dipartimento Di Elettronica-Politecnico Di Milano

Abstract: A combination of distributed computation, positive feedback and constructive greedy heu... more Abstract: A combination of distributed computation, positive feedback and constructive greedy heuristic is proposed as a new approach to stochastic optimization and problem solving. Positive feedback accounts for rapid discovery of very good solutions, distributed computation avoids premature convergence, and greedy heuristic helps the procedure to find acceptable solutions in the early stages of the search process.

. BIBLIOGRAPHY 306

Abstract Dynamic optimisation problems are problems where the search space does not remain consta... more Abstract Dynamic optimisation problems are problems where the search space does not remain constant over time. Evolutionary algorithms aimed at static optimisation problems often fail to effectively optimise dynamic problems. The main reason for this is that the algorithms converge to a single optimum in the search space, and then lack the necessary diversity to locate new optima once the environment changes.

The Swarm-bot Experience: Strength and Mobility through Physical Cooperation

In this chapter, we study a collective robotic system that is inspired by the behavior of social ... more In this chapter, we study a collective robotic system that is inspired by the behavior of social insects. The system consists of mobile robots that can autonomously perceive and modify their environment. We investigate the problem of controlling a number of these robots in cooperation based tasks that are too difficult for the robots to solve when operating alone.

On the performance of ant-based clustering

Abstract. Ant-based clustering and sorting is a nature-inspired heuristic for general clustering ... more Abstract. Ant-based clustering and sorting is a nature-inspired heuristic for general clustering tasks. It has been applied variously, from problems arising in commerce, to circuit design, to text-mining, all with some promise. However, although early results were broadly encouraging, there has been very limited analytical evaluation of the algorithm. Toward this end, we first propose a scheme that enables unbiased interpretation of the clustering solutions obtained, and then use this to conduct a full evaluation of the algorithm.

Towards a theory of practice in meta-heuristics design

Abstract A number of methodological papers published during the last years, testify that a need f... more Abstract A number of methodological papers published during the last years, testify that a need for a thorough revision of the research methodology is felt by the operations research community—see, for example, Barr et al.(1995), Hooker (1995), and Rardin and Uzsoy (2001). In particular, the performance evaluation of nondeterministic methods, such as the methods known as metaheuristics, require the definition of new experimental protocols.

Special Issue: Ant Algorithms

Colonies of social insects can exhibit an amazing variety of complex behaviors and have captured,... more Colonies of social insects can exhibit an amazing variety of complex behaviors and have captured, since ever, the interest of biologists and entomologists. More recently, computer scientists have found in the study of social insects behavior a source of inspiration for the design and implementation of novel distributed multi-agent algorithms. In particular, the study of ant colonies behavior turned out to be very fruitful, giving raise to a completely novel field of research, now known as ant algorithms.

Frankenstein’s PSO: An Engineered Composite Particle Swarm Optimization Algorithm

Abstract We introduce a high-performing composite particle swarm optimization (PSO) algorithm. In... more Abstract We introduce a high-performing composite particle swarm optimization (PSO) algorithm. In an analogy to the popular character of Mary Shelley's famous novel, we call our algorithm Frankenstein's PSO, as it consists of different algorithmic components drawn from other PSO variants. Frankenstein's PSO constituents were selected after careful evaluation of their impact on speed and reliability.

Incremental robot shaping

We propose a modular architecture for autonomous robots which allows for the implementation of ba... more We propose a modular architecture for autonomous robots which allows for the implementation of basic behavioral modules by both programming and training, and accommodates for an evolutionary development of the interconnections among modules. This architecture can implement highly complex controllers and allows for incremental shaping of the robot behavior.

Local search and metaheuristics for the quadratic assignment problem

The quadratic assignment problem (QAP) is an important problem in theory and practice. It was, wh... more The quadratic assignment problem (QAP) is an important problem in theory and practice. It was, which was introduced by Koopmans and Beckmann in 1957 [28] and is a model for many practical problems like backboard wiring [53], campus and hospital layout [15, 17], typewriter keyboard design [9], scheduling [23] and many others [16, 29] can be formulated as QAPs.

SWARM-BOT: Pattern formation in a swarm of self-assembling mobile robots

Abstract We introduce a new robotic system, called swarm-bot. The system consists of a swarm of m... more Abstract We introduce a new robotic system, called swarm-bot. The system consists of a swarm of mobile robots with the ability to connect to/disconnect from each other to self-assemble into different kinds of structures. First, we describe our vision and the goals of the project. Then we present preliminary results on the formation of patterns obtained from a grid-world simulation of the system.

Open e-puck range & bearing miniaturized board for local communication in swarm robotics

Abstract We have designed and built a new open hardware/software board that lets miniaturized rob... more Abstract We have designed and built a new open hardware/software board that lets miniaturized robots communicate and at the same time obtain the range and bearing of the source of emission. The open E-puck Range & Bearing board improves an existing infrared relative localization/communication software library (libIrcom) developed for the e-puck robot and based on its on-board infrared sensors. The board allows the robots to have an embodied, decentralized and scalable communication system.

An insect-based algorithm for the dynamic task allocation problem

An insect-based algorithm inspired by the division of labor in insect colonies is proposed and ap... more An insect-based algorithm inspired by the division of labor in insect colonies is proposed and applied to the solution of an online scheduling problem. A painting facility is considered for illustrating the problem: Trucks leave an assembly line to get painted in painting booths. The goal is to minimize the makespan, that is, the time needed for painting all given trucks. In this paper we address two issues. First, we propose and analyze four modifications of an insect-based algorithm previously introduced by Cicirello and Smith.

Construction Task Allocation through the Collective Perception of a Dynamic Environment

by Yara Khaluf and Marco Dorigo

ANTS, 2020

Building structures is a remarkable collective process but its automation remains an open challen... more Building structures is a remarkable collective process but its automation remains an open challenge. Robot swarms provide a promising solution to this challenge. However, collective construction involves a number of difficulties regarding efficient robots allocation to the different activities, particularly if the goal is to reach an optimal construction rate. In this paper, we study an abstract construction scenario, where a swarm of robots is engaged in a collective perception process to estimate the density of building blocks around a construction site. The goal of this perception process is to maintain a minimum density of blocks available to the robots for construction. To maintain this density, the allocation of robots to the foraging task needs to be adjusted such that enough blocks are retrieved. Our results show a robust collective perception that enables the swarm to maintain a minimum block density under different rates of construction and foraging. Our approach leads the system to stabilize around a state in which the robots allocation allows the swarm to maintain a tile density that is close to or above the target minimum.