Neurosymbolic AI - Why, What, and How
- URL: http://arxiv.org/abs/2305.00813v1
- Date: Mon, 1 May 2023 13:27:22 GMT
- Title: Neurosymbolic AI - Why, What, and How
- Authors: Amit Sheth, Kaushik Roy, Manas Gaur
- Abstract summary: Humans interact with the environment using a combination of perception and cognition.
On the other hand, machine cognition encompasses more complex computations.
This article introduces the rapidly emerging paradigm of Neurosymbolic AI.
- Score: 9.551858963199987
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Humans interact with the environment using a combination of perception -
transforming sensory inputs from their environment into symbols, and cognition
- mapping symbols to knowledge about the environment for supporting
abstraction, reasoning by analogy, and long-term planning. Human
perception-inspired machine perception, in the context of AI, refers to
large-scale pattern recognition from raw data using neural networks trained
using self-supervised learning objectives such as next-word prediction or
object recognition. On the other hand, machine cognition encompasses more
complex computations, such as using knowledge of the environment to guide
reasoning, analogy, and long-term planning. Humans can also control and explain
their cognitive functions. This seems to require the retention of symbolic
mappings from perception outputs to knowledge about their environment. For
example, humans can follow and explain the guidelines and safety constraints
driving their decision-making in safety-critical applications such as
healthcare, criminal justice, and autonomous driving. This article introduces
the rapidly emerging paradigm of Neurosymbolic AI combines neural networks and
knowledge-guided symbolic approaches to create more capable and flexible AI
systems. These systems have immense potential to advance both algorithm-level
(e.g., abstraction, analogy, reasoning) and application-level (e.g.,
explainable and safety-constrained decision-making) capabilities of AI systems.
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