ABLE: A toolkit for building multiagent autonomic systems

被引:61
作者
Bigus, JP
Schlosnagle, DA
Pilgrim, JR
Mills, WN
Diao, Y
机构
[1] IBM Corp, Thomas J Watson Res Ctr, Div Res, Yorktown Hts, NY 10598 USA
[2] IBM Corp, Rochester Custom Technol Ctr, Rochester, MN 55901 USA
关键词
Artificial intelligence - Autonomous agents - Hierarchical systems - [!text type='Java']Java[!/text] programming language - Knowledge representation - Learning systems - Neural networks - Speech recognition;
D O I
10.1147/sj.413.0350
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper describes a toolkit for building multiagent autonomic systems. The IBM Agent Building and Learning Environment (ABLE) provides a lightweight Java(TM) agent framework, a comprehensive JavaBeans(TM) library of intelligent software components, a set of development and test tools, and an agent platform. We describe a series of agents built using ABLE components and present three case studies of applications using the ABLE toolkit. The Autotune agent is a closed-loop controller agent that supports hierarchical distributed control. The Subsumption agent defines specific behaviors or strategies and can be plugged into a multiagent subsumption infrastructure. The Autonomic agent architecture features sensors and effectors for interacting with the external environment, layers of reflexive, reactive, and adaptive subsumption agents, components that dynamically model the autonomic system itself and its environment, and components for emotions, planning, and executive-level decision-making. By using the ABLE component library to build agents running on the ABLE distributed agent platform, we discuss how we can incrementally add new behaviors and capabilities to intelligent, autonomic systems.
引用
收藏
页码:350 / 371
页数:22
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