The Context-Aware Learning Model: experience-powered Logistic Regression Backpropagation (CALM-epLRB)
Joohee Suh, Dean F. Hougen · 2018
To deal with uncertain environments, autonomous agents must learn without supervision. However, reward-based interactive learning often exhibits limitations handling both generalizations and exceptions, and might benefit from explicit recall of past experiences. For these reasons, this research extends the Context-Aware Learning Model (CALM) with a new learning algorithm. CALM-epLRB combines logistic regression backpropagation in artificial neural networks with hyperbolic reward-based learning and a knowledge base that enables experience-powered learning using a novel weight update rule. CALM-epLRB is compared to two previous CALM versions using four metrics on six data sets and shows promising performance.