2019 evolutionary algorithms review
AN Sloss, S Gustafson - Genetic programming theory and practice XVII, 2020 - Springer
Evolutionary algorithm research and applications began over 50 years ago. Like other
artificial intelligence techniques, evolutionary algorithms will likely see increased use and …
artificial intelligence techniques, evolutionary algorithms will likely see increased use and …
[图书][B] Taming uncertainty
An examination of the cognitive tools that the mind uses to grapple with uncertainty in the
real world. How do humans navigate uncertainty, continuously making near-effortless …
real world. How do humans navigate uncertainty, continuously making near-effortless …
Neuroevolution gives rise to more focused information transfer compared to backpropagation in recurrent neural networks
Artificial neural networks (ANNs) are one of the most promising tools in the quest to develop
general artificial intelligence. Their design was inspired by how neurons in natural brains …
general artificial intelligence. Their design was inspired by how neurons in natural brains …
The Elements of Intelligence
C Adami - Artificial Life, 2023 - direct.mit.edu
THE EVOLUTIONARY PATH TO SENTIENT MACHINES COLUMN The Elements of Intelligence
Page 1 THE EVOLUTIONARY PATH TO SENTIENT MACHINES COLUMN The Elements of …
Page 1 THE EVOLUTIONARY PATH TO SENTIENT MACHINES COLUMN The Elements of …
Evolving event-driven programs with SignalGP
A Lalejini, C Ofria - Proceedings of the genetic and evolutionary …, 2018 - dl.acm.org
We present SignalGP, a new genetic programming (GP) technique designed to incorporate
the event-driven programming paradigm into computational evolution's toolbox. Event …
the event-driven programming paradigm into computational evolution's toolbox. Event …
The evolutionary buffet method
Within the field of Genetic Algorithms (GA) and Artificial Intelligence (AI) a variety
computational substrates with the power to find solutions to a large variety of problems have …
computational substrates with the power to find solutions to a large variety of problems have …
Understanding memories of the past in the context of different complex neural network architectures
Deep learning (primarily using backpropagation) and neuroevolution are the preeminent
methods of optimizing artificial neural networks. However, they often create black boxes that …
methods of optimizing artificial neural networks. However, they often create black boxes that …
Evolving autonomous learning in cognitive networks
L Sheneman, A Hintze - Scientific reports, 2017 - nature.com
There are two common approaches for optimizing the performance of a machine: genetic
algorithms and machine learning. A genetic algorithm is applied over many generations …
algorithms and machine learning. A genetic algorithm is applied over many generations …
Towards a theory of mind for artificial intelligence agents
J Schossau, A Hintze - Artificial Life Conference Proceedings 35, 2023 - direct.mit.edu
In the growing fervor around artificial intelligence (AI) old questions have resurfaced
regarding its potential to achieve human-like intelligence and consciousness. A proposed …
regarding its potential to achieve human-like intelligence and consciousness. A proposed …
The structure of evolved representations across different substrates for artificial intelligence
Artificial neural networks (ANNs), while exceptionally useful for classification, are vulnerable
to misdirection. Small amounts of noise can significantly affect their ability to correctly …
to misdirection. Small amounts of noise can significantly affect their ability to correctly …