Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Asynchronous design environments: architecture and behavior
Asynchronous design environments: architecture and behavior
Synergy in cooperating agents: designing manipulators from task specifications
Synergy in cooperating agents: designing manipulators from task specifications
Primary production scheduling at steelmaking industries
IBM Journal of Research and Development
KQML as an agent communication language
Software agents
The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty
ACM Computing Surveys (CSUR)
Cooperative Strategies for Solving the Bicriteria Sparse Multiple Knapsack Problem
Journal of Heuristics
Task Decomposition and Dynamic Role Assignment for Real-Time Strategic Teamwork
ATAL '98 Proceedings of the 5th International Workshop on Intelligent Agents V, Agent Theories, Architectures, and Languages
A Reactive Approach for Solving Constraint Satisfaction Problems
ATAL '98 Proceedings of the 5th International Workshop on Intelligent Agents V, Agent Theories, Architectures, and Languages
The Right Agent (Architecture) to do the Right Thing
ATAL '98 Proceedings of the 5th International Workshop on Intelligent Agents V, Agent Theories, Architectures, and Languages
A Classification Schema to Volumes 1 to 5 of the Intelligent Agents Series
ATAL '98 Proceedings of the 5th International Workshop on Intelligent Agents V, Agent Theories, Architectures, and Languages
The Bases of Effective Coordination in Decentralized Multi-Agent Systems
ATAL '98 Proceedings of the 5th International Workshop on Intelligent Agents V, Agent Theories, Architectures, and Languages
The Right Agent (Architecture) to do the Right Thing
ATAL '98 Proceedings of the 5th International Workshop on Intelligent Agents V, Agent Theories, Architectures, and Languages
Agent-Based Approach to Solving the Resource Constrained Project Scheduling Problem
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
Web Accessible A-Team Middleware
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part III
A-Team Middleware on a Cluster
KES-AMSTA '09 Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
A-Teams and Their Applications
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Population-based algorithm portfolios for numerical optimization
IEEE Transactions on Evolutionary Computation - Special issue on preference-based multiobjective evolutionary algorithms
OptLets: a generic framework for solving arbitrary optimization problems
EC'05 Proceedings of the 6th WSEAS international conference on Evolutionary computing
Adaptive guidance of the search process in evolutionary optimization
CIMMACS'05 Proceedings of the 4th WSEAS international conference on Computational intelligence, man-machine systems and cybernetics
JABAT middleware as a tool for solving optimization problems
Transactions on computational collective intelligence II
Distributed learning with data reduction
Transactions on computational collective intelligence IV
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part III
Agent-based approach to solving difficult scheduling problems
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
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The effectiveness of an agent architecture is measured by its successful application to real problems. In this paper, we describe an agent architecture, A-Teams, that we have successfully used to develop real-world optimization and decision support applications. In an A-Team, an asynchronous team of agents shares a population of solutions and evolves an optimized set of solutions. Each agent embodies its own algorithm for creating, improving or eliminating a solution. Through sharing of the population of solutions, cooperative behavior between agents emerges and tends to result in better solutions than any one agent could produce. Since agents in an A-Team are autonomous and asynchronous, the architecture is both scalable and robust. In order to make the architecture easier to use and more widely available, we have developed an A-Team class library that provides a foundation for creating A-Team based decision-support systems.