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Description
Core Packages | |
com.ibm.able | Refer to the ABLE package index for more details on using ABLE. |
com.ibm.able.beans | The BEANS package provides a set of interfaces and objects which implement "smart" or intelligent components. |
com.ibm.able.beans.bayes | The Bayes package provides a classifer network that uses the Naive Bayes algorithm. |
com.ibm.able.beans.filter | The FILTER package provides a set of objects implementing a template based scaling and transformation of data for use by neural networks. |
com.ibm.able.beans.fuzzy | The Fuzzy System (Fs) package defines a fuzzy rule language, a fuzzy ruleset editor that you can use to create, test, and save source fuzzy rules as well as ready-to-run serialized fuzzy agents (the editor is integrated into the AbleEditor, but also can be run as a stand-alone tool), a fuzzy inference engine, and objects and APIs for creating and running fuzzy rulesets under program control. |
com.ibm.able.beans.rules | The RULES package provides a set of objects implementing standard boolean-logic based forward and backward reasoning using if-then rules. |
com.ibm.able.data | The Data Model package defines.... |
Agent Packages | |
com.ibm.able.agents | The AGENTS package provides a set of interfaces and objects for constructing hybrid intelligent agents out of AbleBean components. |
com.ibm.able.platform | The PLATFORM package provides a set of objects and APIs for running intelligent agents in a distributed environment. |
com.ibm.able.platform.agents | FIPA agents in this package include an AMS, an ACC, and a DF, as well as a default FIPA agent that can be used as a base for building FIPA-compliant agents. |
Graphical Editor | |
com.ibm.able.editor | The EDITOR package provides a set of objects that implement a GUI development environment for constructing hybrid intelligent agents using AbleBeans and AbleAgents as components. |
Examples | |
com.ibm.able.examples | Sample beans and agents are loaded from the ableexamples.jar file and placed on the Samples palette when the Able Agent Editor starts. |
com.ibm.able.examples.ableagent | SimpleAbleAgent - How to create a custom AbleAgent This example shows the easiest method for creating a custom AbleAgent by extending the AbleDefaultAgent base class. |
com.ibm.able.examples.ablebean | SimpleAbleBean - How to create a custom AbleBean This example shows the easiest method for creating a custom AbleBean, by extending the AbleObject base class. There are three java parts that must be created for any AbleBean: The bean class file (SimpleAbleBean.java) The bean info file (SimpleAbleBeanInfo.java) The bean customizer file (SimpleAbleBeanCustomizer.java) To see how the SimpleAbleBean works, go to the Samples panel on the icon palette. Move the mouse slowly over each icon and a tooltip text window will display the name of the bean. Click on the icon for the "SimpleBean". This will create an instance and place it on the canvas. |
com.ibm.able.examples.bayes | The bayesian example package.... |
com.ibm.able.examples.fuzzy | The Fuzzy System (Fs) Examples package contains a number of different types of examples. |
com.ibm.able.examples.genetic | The ABLE genetic examples.... |
com.ibm.able.examples.platform | ABLE PLATFORM examples.... |
The Agent Building and Learning Environment (ABLE) package provides a framework of core Java beans (called AbleBeans) and an IDE (the AbleEditor) for building hybrid remotely-distributable intelligent agents that include both reasoning and learning.
ABLE is a research project at the IBM T.J. Watson Research Center. The focus is on building hybrid intelligent agents that include both reasoning and learning. The ABLE framework consists of a set of core JavaBeans called AbleBeans and a set of function-specific JavaBeans called AbleAgents. Application-level agents (JavaBeans) can be constructed out of these components using the Able Editor or any standard bean builder environment.
The core AbleBeans include beans for reading and writing data from text files, for data transformation and scaling using templates, for rule-based inferencing using boolean and fuzzy logic, and for neural network learning including back propagation and self-organizing maps. The function-specific AbleBeans include agents for classification, clustering, prediction, and genetic search.
As part of the ABLE project, we plan to build a FIPA-compliant agent platform in Java. FIPA, the Foundation for Intelligent Physical Agents, is an international standards body working toward agent interoperability.
Version 1.1 of ABLE is available from the IBM alphaWorks site. You can download code and documentation from alphaWorks.
For more information on the ABLE project, send mail to ableinfo@us.ibm.com.
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ABLE, Version 1.1b | |||||||||
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