A-Teams: An Agent Architecture for Optimization and Decision-Support

Rachlin, John; Goodwin, Richard; Murthy, Sesh; Akkijaru, Rama; Wu, Frederick Y.; Kumaran, Santhosh; Das, Raja

doi:10.1007/3-540-49057-4_17

Cited by 43 publications

(21 citation statements)

References 10 publications

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“…In such extended fusion schemes, the resulting system contains only SC constituents that are being implemented in an HC framework, or only HC constituents that are being embedded in an SC framework. Representative examples of such fusions are: genetic algorithms formulated in an objectoriented framework [35]; fuzzy rules coded in a Petri net [36]; neural networks embedded in inverse-model-based control techniques [37]; and various mathematical programming methods combined in a genetic algorithm architecture [38]. …”

Section: Stochastic System Simulatorsmentioning

confidence: 99%

Editor's Introduction to Chapter 10

Ovaska¹

2004

Computationally Intelligent Hybrid Systems

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Section: Stochastic System Simulatorsmentioning

confidence: 99%

Editor's Introduction to Chapter 10

Ovaska¹

2004

Computationally Intelligent Hybrid Systems

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“…Liu and Teng [6] presented a human-algorithm-knowledge based human-computer cooperative layout method to solve a satellite module layout problem. In addition, Murthy [7] proposed an asynchronous team framework which substituted the algorithm operators.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective Human-computer Co-operative Co-evolutionary Method Based on Non-dominated Sorting Strategy

Huo¹,

Chen²,

Jianjun³

et al. 2014

TOEEJ

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Based on the human-computer cooperation ideas, a Human-Computer Multi-Objective Cooperative Co-Evolutionary Method (HCMCCM) is developed to solve the complex engineering layout problem, in which the multiobjective optimization idea is integrated to avoid the "flooding" phenomenon that occurs during the combination of the artificial solutions and the algorithm solutions. In the proposed HCMCCM, the artificial solutions expressed by unified encoding strings are incorporated together with the algorithms solutions to create new cooperative solutions based on the non-dominated sorting strategies. This kind of cooperation can make the artificial solutions and the algorithm solutions on an equal basis and integrate the artificial individual with the individual algorithms into a multi-objective trade-off. The numerical simulation results of the satellite layout problem show that the proposed method can combine the artificial solutions and the algorithm solutions effectively and provide a Pareto solution set for engineers to choose from.

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“…It has been shown that the A-Team framework enables users to easily combine disparate problem solving strategies, each in the form of an autonomous agent, and enables these agents to cooperate to evolve diverse and high quality solutions [14]. Acording to [15] an asynchronous team is a collection of software agents that solve a problem by dynamically evolving a population of solutions.…”

Section: Introductionmentioning

confidence: 99%

“…Among platforms and environments used to implement A-Team concept some well known include IBM A-Team written in C++ with own configuration language [14] and Bang 3 -a platform for the development of Multi-Agent Systems (MAS) [12]. Some implementations of A-Team were based on universal tools like Matlab [16].…”

Section: Introductionmentioning

confidence: 99%