Justification-based case retention
A CBR system needs a good case retention strategy to decide which cases to incorporate into the case base in order to maximize the performance of the system. In this work we present a collaborative case retention strategy, designed for multiagent CBR systems, called the Collaborative Case Bargaining...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2004 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/160822 |
| Acceso en línea: | http://hdl.handle.net/10261/160822 |
| Access Level: | acceso abierto |
| Palabra clave: | Case-based reasoning CBR systems |
| Sumario: | A CBR system needs a good case retention strategy to decide which cases to incorporate into the case base in order to maximize the performance of the system. In this work we present a collaborative case retention strategy, designed for multiagent CBR systems, called the Collaborative Case Bargaining strategy. The CCB strategy is a bargaining mechanism in which each CBR agent tries to maximize the utility of the cases it retains. We will present a case utility measure called the Justification-based Case Utility (JCU) based upon the ability of the individual CBR agents to provide justifications of their own results. An empirical evaluation of the CCB strategy shows the benefits for CBR agents to use this strategy: individual and collective accuracy are increased while the size of the case bases is decreased. © Springer-Verlag 2004. |
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