Empirical experiments have shown that storing every case does not automatically improve the accuracy of a CBR system. Therefore, several retain policies have been proposed in order to select which cases to retain. However, all the research done in case retention strategies is done in centralized CBR systems. We focus on multiagent CBR systems, where each agent has a local case base, and where e...

in electronic commerce markets, agents often should acquire multiple resources to fulfil a high-level task. in order to attain such resources they need to compete with each other. in multi-agent environments, in which competition is involved, negotiation would be an interaction between agents in order to reach an agreement on resource allocation and to be coordinated with each other. in recent ...

Abs t r ac t . VS-CBR [14] is a simple instance-based learning algorithm that adjusts a weighted similarity measure as well as collecting cases. This paper presents a 'PAC' analysis of VS-CBR, motivated by the PAC learning framework, which demonstrates two main ideas relevant to the study of instance-based learners. Firstly, the hypothesis spaces of a learner on different target concepts can be...

The Utility Problem for Lazy Learners Towards a Non-eager Approach p. 141 EGAL: Exploration Guided Active Learning for TCBR p. 156 Introspective Knowledge Revision in Textual Case-Based Reasoning p. 171 A General Introspective Reasoning Approach to Web Search for Case Adaptation p. 186 Detecting Change via Competence Model p. 201 CBTV: Visualising Case Bases for Similarity Measure Design and Se...

During the design phase of a textual case-based reasoning (TCBR) system, decisions have to be made regarding the internal representation of the cases and the similarity metrics. Such decisions have a significant impact on the performance of the resulting TCBR system. We believe that guidance should be provided to the designer during the authoring process. Unfortunately most of the metrics propo...

We present a novel approach to mine word similarity in Textual Case Based Reasoning. We exploit indirect associations of words, in addition to direct ones for estimating their similarity. If word A co-occurs with word B, we say A and B share a first order association between them. If A co-occurs with B in some documents, and B with C in some others, then A and C are said to share a second order...

In Case-Based Reasoning and in Machine Learning, an important concept is the similarity metric (or measure), a function which rates how similar two objects are, according to some criteria. We concentrate here on case-base queries – finding a case in a case-base which most resembles some probe case. Selecting what metrics are most appropriate is a key part of both designing, and using, a case-base.

Risk response is an important work in project risk management (PRM). To generate project risk response strategies, retrieving and reusing information and knowledge of the similar historical cases is important, while research concerning this issue is still relatively scarce. Taking the risk response of the subway project in S city, China as a case problem, this paper proposes a pragmatic method ...