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This paper presents a novel learning model CLARION, which is a hybrid model based on the two-level approach proposed by Sun. The model integrates neural, reinforcement, and symbolic learning methods to perform on-line, bottom-up learning (i.e., learning that goes from neural to symbolic representations). The model utilizes both procedural and declarative(More)
To deal with reactive sequential decision tasks, we present a learning model Clarion, which is a hybrid connectionist model consisting of both localist and distributed representations, based on the two-level approach proposed in Sun (1995). The model learns and utilizes procedural and declarative knowledge , tapping into the synergy of the two types of(More)
BACKGROUND Type III paraesophageal hernias are diaphragmatic defects with the risk of serious complications. High recurrence rates associated with primary suture repair are significantly improved with the use of a tension-free repair with prosthetic mesh. However, mesh in the hiatus is associated with multiple complications. A bio-engineered material from(More)
We present a skill learning model CLARION. Different from existing models of high-level skill learning that use a top-down approach (that is, turning declarative knowledge into procedural knowledge), we adopt a bottom-up approach toward low-level skill learning, where procedural knowledge develops first and declarative knowledge develops later. CLAR-ION is(More)
This paper addresses weighting and partitioning in complex reinforcement learning tasks, with the aim of facilitating learning. The paper presents some ideas regarding weighting of multiple agents and extends them into partitioning an input/state space into multiple regions with diierential weighting in these regions, to exploit diierential characteristics(More)
Chromosomal amplifications and deletions are critical components of tumorigenesis and DNA copy-number variations also correlate with changes in mRNA expression levels. Genome-wide microarray comparative genomic hybridization (CGH) has become an important method for detecting and mapping chromosomal changes in tumors. Thus, the ability to detect twofold(More)