Douglas S. Blank, Joshua M. Lewis, and James B. Marshall
Anticipatory systems have been shown to be useful in discrete, symbolic systems. However, non-symbolic anticipatory systems are less well understood. In this paper, we explore the use of anticipation within the framework of connectionist networks to bootstrap from an innate behavior; to drive a reinforcement signal; and to provide feedback on the learnability of a task.
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