Symbolic Artificial Intelligence (AI) is a subfield of AI that focuses on the processing and manipulation of symbols or concepts, rather than numerical data. The goal of Symbolic AI is to build intelligent systems that can reason and think like humans by representing and manipulating knowledge and...
Abstract Basic methodological assumptions of methods which belong to symbolic Artificial Intelligence are presented in this chapter.This is a preview of subscription content, log in via an institution to check access. Notes 1. For example, knowledge is defined in the form of graphs, logic formulas...
Today, artificial intelligence is mostly aboutartificial neural networksanddeep learning. But this is not how it always was. In fact, for most of its six-decade history, the field was dominated by symbolic artificial intelligence, also known as “classical AI,”“rule-based AI,” and “good ...
Here we use Monte Carlo tree search and symbolic artificial intelligence (AI) to discover retrosynthetic routes. We combined Monte Carlo tree search with an expansion policy network that guides the search, and a filter network to pre-select the most promising retrosynthetic steps. These deep neural...
Artificial intelligence (AI) provides general methods and tools for the automated solving of such problems.We start our contribution with a discussion of the relation between AI and analytics techniques. As many decision and optimization problems are computationally complex, we present the challenges ...
AIKA (Artificial Intelligence for Knowledge Acquisition) is an innovative approach to neural network design, diverging from traditional architectures that rely heavily on rigid matrix and vector operations. The AIKA Project introduces a flexible, sparse, and non-layered network representation, derived from...
This has led to several significant milestones in artificial intelligence, giving rise to deep learning models that, for example, could beat humans in progressively complex games, including Go and StarCraft. But it can be challenging to reuse these deep learning models or extend them to...
Neuro-Symbolic AI is a burgeoning field that marries two distinct realms of artificial intelligence: neural networks, which form the core of deep learning, and symbolic AI, which encompasses logic-based and knowledge-based systems. This synergy is designed to capitalize on the strengths of each ...
Shakey the Robot: The First Robot to Embody Artificial Intelligence If the brain is analogous to a computer, this means that every situation we encounter relies on us running an internal computer program which explains, step by step, how to carry out an operation, based entirely on logic. Pro...
Neuro-symbolic programming is a paradigm for artificial intelligence and cognitive computing that combines the strengths of both deep neural networks and symbolic reasoning.Deep neural networks are a type of machine learning algorithms that are inspired by the structure and function of biological neural...