ACI Journal Articles

Document Type

Conference Proceeding

USMA Research Unit Affiliation

Army Cyber Institute

Publication Date

2-15-2018

Abstract

The work presented is an evaluation of a method for developing a hybrid system, consisting of a Deep Reinforcement Learning (RL) agent and a cognitive model, capable of providing explanations of its action decisions. The methodology uses a symbolic/sub-symbolic cognitive architecture to introspection the activity of the network to understand its representation. The entropy in the system’s behavioral predictions could be used as a signal to affirm or deny ascribing a representation to the network.

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