ABLE

ABLE: A toolkit for building multiagent autonomic systems. This paper describes a toolkit for building multiagent autonomic systems. The IBM Agent Building and Learning Environment (ABLE) provides a lightweight Java™ agent framework, a comprehensive JavaBeans™ 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.


References in zbMATH (referenced in 4 articles )

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  1. Gadioli, Davide; Vitali, Emanuele; Palermo, Gianluca; Silvano, Cristina: mARGOt: a dynamic autotuning framework for self-aware approximate computing (2019)
  2. Psaier, Harald; Dustdar, Schahram: A survey on self-healing systems: Approaches and systems (2011) ioport
  3. Alberola, Juan M.; Such, Jose M.; Garcia-Fornes, Ana; Espinosa, Agustin; Botti, Vicent: A performance evaluation of three multiagent platforms (2010) ioport
  4. Bigus, Joseph P.; Schlosnagle, Don A.; Pilgrim, Jeff R.; Iii, W. Nathaniel Mills; Diao, Yixin: ABLE: A toolkit for building multiagent autonomic systems. (2002) ioport