Collaborative Autonomous Learning Systems
Plamen Parvanov Angelov · 2012
This chapter briefly describes the powerful and interesting idea of the team of autonomous learning system (ALS) that can collaborates. In a collaborative scenario, each ALS acts on its own pursuing its own objectives and goals, but they can collaborate to achieve a common, shared goal. There can, broadly, be two different modes of operation: centralised collaborative ALSs and decentralised collaborative ALSs. Autonomous systems can collaborate while performing their mission in terms of any or a combination of the tasks. Some tasks include: density estimation and clustering of the incoming sensory data, prediction, filtering, estimation, self-calibrating inferential sensors and classification. The chapter discusses the collaborative autonomous clustering, and AutoCluster by a team of ALSs, and the collaborative autonomous predictors, estimators, filters and AutoSense by a team of ALSs. It also discusses the collaborative autonomous classifiers AutoClassify by a team of ALSs. Controlled Vocabulary Terms learning systems; pattern classification; pattern clustering; sensors