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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 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 processes. It(More)
In developing autonomous agents, one usually emphasizes only (situated) procedural knowledge, ignoring more explicit declarative knowledge. On the other hand, in developing symbolic reasoning models, one usually emphasizes only declarative knowledge, ignoring procedural knowledge. In contrast, we have developed a learning model Clarion, which is a hybrid(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)