Finally, their operation is largely opaque to humans, rendering them unsuitable for domains in which verifiability is important. In this paper, we propose an end-to-end reinforcement learning architecture comprising a neural back end and a symbolic front end with the potential to overcome each of these shortcomings. As proof-of-concept, we present a preliminary implementation of the architecture and apply it to several variants of a simple video game.
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Everything you wanted to know about AI – but were afraid to ask – The Guardian
Everything you wanted to know about AI – but were afraid to ask.
Posted: Fri, 24 Feb 2023 22:00:00 GMT [source]
