Asynchronous Teams

Talukdar, Sarosh N.; Murthy, Sesh; Akkiraju, Rama

doi:10.1007/0-306-48056-5_19

Cited by 30 publications

(14 citation statements)

References 10 publications

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“…Such peer-to-peer combinations of exact/heuristic techniques are less frequent. An interesting framework for this purpose was proposed by Talukdar et al [38,39] with the so-called asynchronous teams (A-Teams). An A-Team is a problem solving architecture consisting of a collection of agents and memories connected into a strongly cyclic directed network.…”

Section: Parallel or Intertwined Executionmentioning

confidence: 99%

See 1 more Smart Citation

Combining Metaheuristics and Exact Algorithms in Combinatorial Optimization: A Survey and Classification

Puchinger

Raidl

2005

Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired Approach

217

118

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Abstract. In this survey we discuss different state-of-the-art approaches of combining exact algorithms and metaheuristics to solve combinatorial optimization problems. Some of these hybrids mainly aim at providing optimal solutions in shorter time, while others primarily focus on getting better heuristic solutions. The two main categories in which we divide the approaches are collaborative versus integrative combinations. We further classify the different techniques in a hierarchical way. Altogether, the surveyed work on combinations of exact algorithms and metaheuristics documents the usefulness and strong potential of this research direction.

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Section: Parallel or Intertwined Executionmentioning

confidence: 99%

“…A-Teams have been successfully utilized in a variety of combinatorial optimization problems, see e.g. [5,39]. Denzinger and Offerman [12] present a similar multi-agent based approach for achieving cooperation between search-systems with different search paradigms.…”

Section: Parallel or Intertwined Executionmentioning

confidence: 99%

Combining Metaheuristics and Exact Algorithms in Combinatorial Optimization: A Survey and Classification

Puchinger

Raidl

2005

Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired Approach

217

118

View full text Add to dashboard Cite

show abstract

“…The most popular model for asynchronous distributed algorithms is called A-teams, where A stands for asynchronous [12]. A-Teams combine different algorithms that share a memory in closed loops and are a way of specifying data flow among different methods to solve a problem.…”

Section: State Of the Artmentioning

confidence: 99%

Pool vs. Island Based Evolutionary Algorithms: An Initial Exploration

Merelo

Mora

Fernandes

et al. 2012

2012 Seventh International Conference on P2P, Parallel, Grid, Cloud and Internet Computing

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Abstract-This paper explores the scalability and performance of pool and island based evolutionary algorithms, both of them using as a mean of interaction an object store; we call this family of algorithms SofEA. This object store allows the different clients to interact asynchronously; the point of the creation of this framework is to build a system for spontaneous and voluntary distributed evolutionary computation. The fact that each client is autonomous leads to a complex behavior that will be examined in the work, so that the design can be validated, rules of thumb can be extracted, and the limits of scalability can be found. In this paper we advance the design of an asynchronous, fault-tolerant and scalable distributed evolutionary algorithm based on the object store CouchDB. We test experimentally the different options and show the trade-offs that pool and island-based solutions offer.

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“…Apart from these systems of reactive agents, there has been an organizational model of Asynchronous Team (A-Team) proposed in [47]. A-Team consists of autonomous agents each of which can choose what to do and when to communicate with its team mates, if ever.…”

Section: Related Workmentioning

confidence: 99%

Collective Problem Solving through Coordination in a Society of Reactive Agents

Liu¹

1994

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Asynchronous Teams

Cited by 30 publications

References 10 publications

Combining Metaheuristics and Exact Algorithms in Combinatorial Optimization: A Survey and Classification

Combining Metaheuristics and Exact Algorithms in Combinatorial Optimization: A Survey and Classification

Pool vs. Island Based Evolutionary Algorithms: An Initial Exploration

Collective Problem Solving through Coordination in a Society of Reactive Agents

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