Results 1 - 10
of
91
A taxonomy for multi-agent robotics
- AUTONOMOUS ROBOTS
, 1996
"... A key difficulty in the design of multi-agent robotic systems is the size and complexity of the space of possible designs. In order to make principled design decisions, an understanding of the many possible system configurations is essential. To this end, we present a taxonomy that classifies multia ..."
Abstract
-
Cited by 97 (6 self)
- Add to MetaCart
(Show Context)
A key difficulty in the design of multi-agent robotic systems is the size and complexity of the space of possible designs. In order to make principled design decisions, an understanding of the many possible system configurations is essential. To this end, we present a taxonomy that classifies multiagent systems according to communication, computational and other capabilities. We survey existing efforts involving multi-agent systems according to their positions in the taxonomy. We also present additional results concerning multi-agent systems, with the dual purposes of illustrating the usefulness of the taxonomy in simplifying discourse about robot collective properties, and also demonstrating that a collective can be demonstrably more powerful than a single unit of the collective.
Building Multirobot Coalitions Through Automated Task Solution Synthesis -- A group of robots can move to, or push boxes to, specified locations by sharing information when individual robots cannot perform the tasks separately
, 2006
"... This paper presents a reasoning system that enables a group of heterogeneous robots to form coalitions to accomplish a multirobot task using tightly coupled sensor sharing. Our approach, which we call ASyMTRe, maps environmental sensors and perceptual and motor control schemas to the required flow ..."
Abstract
-
Cited by 56 (16 self)
- Add to MetaCart
This paper presents a reasoning system that enables a group of heterogeneous robots to form coalitions to accomplish a multirobot task using tightly coupled sensor sharing. Our approach, which we call ASyMTRe, maps environmental sensors and perceptual and motor control schemas to the required flow of information through the multirobot system, automatically reconfiguring the connections of schemas within and across robots to synthesize valid and efficient multirobot behaviors for accomplishing a multirobot task. We present the centralized anytime ASyMTRe configuration algorithm, proving that the algorithm is correct, and formally addressing issues of completeness and optimality. We then present a distributed version of ASyMTRe, called ASyMTRe-D, which uses communication to enable distributed coalition formation. We validate the centralized approach by applying the ASyMTRe methodology to two application scenarios: multirobot transportation and multirobot box pushing. We then validate the ASyMTRe-D implementation in the multirobot transportation task, illustrating its fault-tolerance capabilities. The advantages of this new approach are that it: 1) enables robots to synthesize new task solutions using fundamentally different combinations of sensors and effectors for different coalition compositions and 2) provides a general mechanism for sharing sensory information across networked robots.
Towards Multi-Swarm Problem Solving in Networks
- IN PROCEEDINGS OF THIRD INTERNATIONAL CONFERENCE ON MULTI-AGENT SYSTEMS (ICMAS'98
, 1998
"... This paper describes how multiple interacting swarms of adaptive mobile agents can be used to solve problems in networks. The paper introduces a new architectural description for an agent that is chemically inspired and proposes chemical interaction as the principal mechanism for inter-swarm communi ..."
Abstract
-
Cited by 44 (4 self)
- Add to MetaCart
This paper describes how multiple interacting swarms of adaptive mobile agents can be used to solve problems in networks. The paper introduces a new architectural description for an agent that is chemically inspired and proposes chemical interaction as the principal mechanism for inter-swarm communication. Agents within a given swarm have behavior that is inspired by the foraging activities of ants, with each agent capable of simple actions and knowledge of a global goal is not assumed. The creation of chemical trails is proposed as the primary mechanism used in distributed problem solving arising from self-organization of swarms of agents. The paper proposes that swarm chemistries can be engineered in order to apply the principal ideas of the Subsumption Architecture in the domain of mobile agents. The paper presents applications of the new architecture in the domain of communications networks and describes the essential elements of a mobile agent framework that is being considered fo...
Stability analysis of one-dimensional asynchronous swarms
- In American Control Conference
, 2001
"... Abstract—Coordinated swarm behavior in certain types of animals can also occur in groups of autonomous vehicles. Swarm “cohesiveness” is characterized as a stability property. Conditions for one-dimensional asynchronous swarms to achieve collision-free convergence even in the presence of sensing del ..."
Abstract
-
Cited by 39 (6 self)
- Add to MetaCart
(Show Context)
Abstract—Coordinated swarm behavior in certain types of animals can also occur in groups of autonomous vehicles. Swarm “cohesiveness” is characterized as a stability property. Conditions for one-dimensional asynchronous swarms to achieve collision-free convergence even in the presence of sensing delays and asynchronism during movements are provided. Each finite-size swarm member has proximity sensors and neighbor position sensors that only provide delayed position information. Such stability analysis is of fundamental importance if one wants to understand the coordination mechanisms for “platoons ” of autonomous vehicles, where intermember communication channels are less than perfect and collisions must be avoided. Index Terms—Asynchronism, communication delay, discrete-event systems, stability, swarms. I.
Distributed intelligence: Overview of the field and its application in multi-robot systems
- Journal of Physical Agents
, 2008
"... Abstract—This article overviews the concepts of distributed intelligence, outlining the motivations for studying this field of research. First, common systems of distributed intelligence are classified based upon the types of interactions exhibited, since the type of interaction has relevance to the ..."
Abstract
-
Cited by 38 (1 self)
- Add to MetaCart
(Show Context)
Abstract—This article overviews the concepts of distributed intelligence, outlining the motivations for studying this field of research. First, common systems of distributed intelligence are classified based upon the types of interactions exhibited, since the type of interaction has relevance to the solution paradigm to be used. We outline three common paradigms for distributed intelligence — the bioinspired paradigm, the organizational and social paradigm, and the knowledge-based, ontological paradigm — and give examples of how these paradigms can be used in multi-robot systems. We then look at a common problem in multirobot systems — that of task allocation — and show how the solution approach to this problem is very different depending upon the paradigm chosen for abstracting the problem. Our conclusion is that the paradigms are not interchangeable, but rather the selection of the appropriate paradigm is dependent
Evolution and Development of Control Architectures in Animats
, 1996
"... This paper successively describes the works of Boers & Kuiper, Gruau, Cangelosi et al., Vaario, Dellaert & Beer, and Sims, which all evolve the developmental program of an artificial nervous system. The potentialities of these approaches for automatically devising a control architecture link ..."
Abstract
-
Cited by 35 (14 self)
- Add to MetaCart
This paper successively describes the works of Boers & Kuiper, Gruau, Cangelosi et al., Vaario, Dellaert & Beer, and Sims, which all evolve the developmental program of an artificial nervous system. The potentialities of these approaches for automatically devising a control architecture linking the perceptions and the actions of an animat are then discussed, together with their possible contributions to the fundamental issue of assessing the adaptive values of development, learning and evolution.
ASGA: Improving the Ant System by Integration with Genetic Algorithms
- UNIVERSITY OF WISCONSIN
, 1998
"... This paper describes how the Ant System can be improved by self-adaptation of its controlling parameters. Adaptation is achieved by integrating a genetic algorithm with the ant system and maintaining a population of agents (ants) that have been used to generate solutions. These agents have be ..."
Abstract
-
Cited by 30 (2 self)
- Add to MetaCart
This paper describes how the Ant System can be improved by self-adaptation of its controlling parameters. Adaptation is achieved by integrating a genetic algorithm with the ant system and maintaining a population of agents (ants) that have been used to generate solutions. These agents have behavior that is inspired by the foraging activities of ants, with each agent capable of simple actions. Problem solving is inherently distributed and arises as a consequence of the self-organization of a collection of agents, or swarm system. This paper applies the Ant System with Genetic Algorithm (ASGA) system to the problem of path finding in networks, demonstrating by experimentation that the hybrid algorithm exhibits improved performance when compared to the basic Ant System.
Swarm Intelligence Algorithms for Data Clustering
- IN SOFT COMPUTING FOR KNOWLEDGE DISCOVERY AND DATA MINING BOOK, PART IV
"... Clustering aims at representing large datasets by a fewer number of prototypes or clusters. It brings simplicity in modeling data and thus plays a central role in the process of knowledge discovery and data mining. Data mining tasks, in these days, require fast and accurate partitioning of huge da ..."
Abstract
-
Cited by 26 (1 self)
- Add to MetaCart
(Show Context)
Clustering aims at representing large datasets by a fewer number of prototypes or clusters. It brings simplicity in modeling data and thus plays a central role in the process of knowledge discovery and data mining. Data mining tasks, in these days, require fast and accurate partitioning of huge datasets, which may come with a variety of attributes or features. This, in turn, imposes severe computational requirements on the relevant clustering techniques. A family of bio-inspired algorithms, well-known as Swarm Intelligence (SI) has recently emerged that meets these requirements and has successfully been applied to a number of real world clustering problems. This chapter explores the role of SI in clustering different kinds of datasets. It finally describes a new SI technique for partitioning any dataset into an optimal number of groups through one run of optimization. Computer simulations undertaken in this research have also been provided to demonstrate the effectiveness of the proposed algorithm.
Y.: Fireworks algorithm for optimization
- ICSI 2010. LNCS
, 2010
"... Abstract. Inspired by observing fireworks explosion, a novel swarm in-telligence algorithm, called Fireworks Algorithm (FA), is proposed for global optimization of complex functions. In the proposed FA, two types of explosion (search) processes are employed, and the mechanisms for keeping diversity ..."
Abstract
-
Cited by 25 (22 self)
- Add to MetaCart
(Show Context)
Abstract. Inspired by observing fireworks explosion, a novel swarm in-telligence algorithm, called Fireworks Algorithm (FA), is proposed for global optimization of complex functions. In the proposed FA, two types of explosion (search) processes are employed, and the mechanisms for keeping diversity of sparks are also well designed. In order to demon-strate the validation of the FA, a number of experiments were conducted on nine benchmark test functions to compare the FA with two vari-ants of particle swarm optimization (PSO) algorithms, namely Standard PSO and Clonal PSO. It turns out from the results that the proposed FA clearly outperforms the two variants of the PSOs in both convergence speed and global solution accuracy.
Connection Management using Adaptive Mobile Agents
- Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA'98
, 1998
"... : This paper describes how adaptive mobile agents can be used to solve connection management problems in Telecommunications using a parallel, distributed process. These agents have behavior that is inspired by the foraging activities of ants, with each agent capable of simple actions. Problem solvin ..."
Abstract
-
Cited by 25 (5 self)
- Add to MetaCart
(Show Context)
: This paper describes how adaptive mobile agents can be used to solve connection management problems in Telecommunications using a parallel, distributed process. These agents have behavior that is inspired by the foraging activities of ants, with each agent capable of simple actions. Problem solving is distributed and arises as a consequence of the self-organization of a collection of agents, or swarm system. Such swarm systems are frequently highly sensitive to their own control parameters and hence it is desirable to have the parameters self adapt using feedback from their environment. This paper presents an adaptive mechanism that allows agents to vary control parameters based upon the routing solutions obtained. Results of the simulation of these algorithms are presented. Keywords: mobile agents, routing, network management, swarm intelligence 1. Introduction The notion of complex collective behavior emerging from the behavior of many simple agents and their interactions is ce...
