An agent-based operational model for hybrid connectionist-symbolic learning
Hybridization of connectionist and symbolic systems is being proposed for machine learning purposes in many applications for different fields. However, a unified framework to analyse and compare learning methods has not appeared yet. In this paper, a multiagent-based approach is presented as an adequate model for hybrid learning. This approach is built upon the concept of bias.
KeywordsUnify Framework Tactical Level Majority Vote Scheme Bias Management Search Bias
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