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Neurosymbolic Programming (Paperback)
Loot Price: R1,661
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Neurosymbolic Programming (Paperback)
Series: Foundations and Trends (R) in Programming Languages
Expected to ship within 10 - 15 working days
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Neurosymbolic programming is an emerging area that bridges the
areas of deep learning and program synthesis. As in classical
machine learning, the goal is to learn functions from data.
However, these functions are represented as programs that can use
neural modules in addition to symbolic primitives and are induced
using a combination of symbolic search and gradient-based
optimization. Neurosymbolic programming can offer multiple
advantages over end-to-end deep learning. Programs can sometimes
naturally represent long-horizon, procedural tasks that are
difficult to perform using deep networks. Neurosymbolic
representations are also, commonly, easier to interpret and
formally verify than neural networks. The restrictions of a
programming language can serve as a form of regularization and lead
to more generalizable and data-efficient learning. Compositional
programming abstractions can also be a natural way of reusing
learned modules across learning tasks.In this monograph, the
authors illustrate these potential benefits with concrete examples
from recent work on neurosymbolic programming. They also categorize
the main ways in which symbolic and neural learning techniques come
together in this area and conclude with a discussion of the open
technical challenges in the field. The comprehensive review of
neurosymbolic programming introduces the reader to the topic and
provides an insightful treatise on an increasingly important topic
at the intersection of programming languages and machine learning.
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