Neuro-symbolic artificial intelligence: The state of the art
Neuro-symbolic AI is an emerging subfield of Artificial Intelligence that brings together two
hitherto distinct approaches.” Neuro” refers to the artificial neural networks prominent in …
hitherto distinct approaches.” Neuro” refers to the artificial neural networks prominent in …
Chapter 1. Neural-Symbolic Learning and Reasoning: A Survey and Interpretation 1
The study and understanding of human behaviour is relevant to computer science, artificial
intelligence, neural computation, cognitive science, philosophy, psychology, and several …
intelligence, neural computation, cognitive science, philosophy, psychology, and several …
Recognition and localization of relevant human behavior in videos
Ground surveillance is normally performed by human assets, since it requires visual
intelligence. However, especially for military operations, this can be dangerous and is very …
intelligence. However, especially for military operations, this can be dangerous and is very …
Artificial development of biologically plausible neural-symbolic networks
Neural-symbolic networks are neural networks designed for the purpose of representing
logic programs. One of the motivations behind this is to work towards a biologically plausible …
logic programs. One of the motivations behind this is to work towards a biologically plausible …
Applying Neural-Symbolic Cognitive Agents in Intelligent Transport Systems to reduce CO2 emissions
Providing personalized feedback in Intelligent Transport Systems is a powerful tool for
instigating a change in driving behaviour and the reduction of CO 2 emissions. This requires …
instigating a change in driving behaviour and the reduction of CO 2 emissions. This requires …
Dreaming Machines: On multimodal fusion and information retrieval using neural-symbolic cognitive agents
L de Penning, A D'Avila Garcez… - 2013 Imperial College …, 2013 - drops.dagstuhl.de
Abstract Deep Boltzmann Machines (DBM) have been used as a computational cognitive
model in various AI-related research and applications, notably in computational vision and …
model in various AI-related research and applications, notably in computational vision and …
Instructional Strategies for Scenario-Based Training of Human Behavior Cue Analysis with Robot-Aided Intelligence, Surveillance, Reconnaissance
J Salcedo - 2014 - stars.library.ucf.edu
The US Army desires to improve safety during Intelligence, Surveillance, Reconnaissance
(ISR) operations by removing Warfighters from direct line-of-fire by enhancing ISR …
(ISR) operations by removing Warfighters from direct line-of-fire by enhancing ISR …
[PDF][PDF] Neural-symbolic cognitive agents: architecture, theory and application
In real-world applications, the effective integration of learning and reasoning in a cognitive
agent model is a difficult task. However, such integration may lead to a better understanding …
agent model is a difficult task. However, such integration may lead to a better understanding …
[BOOK][B] Artificial Development of Neural-Symbolic Networks
JP Townsend - 2014 - search.proquest.com
Artificial neural networks (ANNs) and logic programs have both been suggested as means
of modelling human cognition. While ANNs are adaptable and relatively noise resistant, the …
of modelling human cognition. While ANNs are adaptable and relatively noise resistant, the …