Fetching the paper…
Reading the bibliography…
In the last couple of years, the rise of Artificial Intelligence and the successes of academic breakthroughs in the field have been inescapable.
Computing machinery and intelligence
A. M. Turing · 1950
Earlier work this paper cites.
Pattern recognition and modern computers
Oliver G Selfridge · 1955
Earlier work this paper cites.
The perceptron: A perceiving and recognizing automaton
Frank Rosenblatt · 1957
Earlier work this paper cites.
Heuristic problem solving: The next advance in operations research
Herbert A. Simon and Allen Newell · 1958
Earlier work this paper cites.
Minds and machines
Hilary Putnam · 1960
Earlier work this paper cites.
Alchemy and Artificial Intelligence
H.L. Dreyfus · 1965
Earlier work this paper cites.
Perceptrons: An Introduction to Computational Geometry
Marvin Minsky and Seymour Papert · 1969
Earlier work this paper cites.
The metaphorical brain: an introduction to cybernetics as artificial intelligence and brain theory
M.A. Arbib · 1972
Earlier work this paper cites.
Cognitive representations of semantic categories
Eleanor Rosch · 1975
Earlier work this paper cites.
On the stochastic dynamics of neuronal interaction
T. J. Sejnowski · 1976
Earlier work this paper cites.
On the adequacy of prototype theory as a theory of concepts
Daniel N. Osherson and Edward E. Smith · 1981
Earlier work this paper cites.
R1: A rule-based configurer of computer systems
John McDermott · 1982
Earlier work this paper cites.
The knowledge level
Allen Newell et al · 1982
Earlier work this paper cites.
Science Observed: Perspectives on the Social Study of Science
Harry Collins · 1983
Earlier work this paper cites.
Building Expert Systems
Frederick Hayes-Roth, Donald A. Waterman, and Douglas B. Lenat · 1983
Earlier work this paper cites.
Expert Systems Techniques, Tools and Applications
Philip Klahr and Donald A. Waterman, editors · 1986
Earlier work this paper cites.
CYC: using common sense knowledge to overcome brittleness and knowledge acquisition bottlenecks
Douglas B. Lenat, Mayank Prakash, and Mary Shepherd · 1986
Earlier work this paper cites.
Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Vol. 1, Vol. 2
D. E. Rumelhart and J. L. McClelland · 1986
Earlier work this paper cites.
A massively parallel architecture for a self-organizing neural pattern recognition machine
Gail A. Carpenter and Stephen Grossberg · 1987
Earlier work this paper cites.
The constituent structure of connectionist mental states
Paul Smolensky · 1987
Cited alongside, same era.
Making a Mind versus Modeling the Brain: Artificial Intelligence Back at a Branchpoint
Hubert L. Dreyfus and Stuart E. Dreyfus · 1988
Cited alongside, same era.
Connectionism and cognitive architecture: A critical analysis
Jerry A. Fodor and Zenon W. Pylyshyn · 1988
Cited alongside, same era.
Nonlinear neural networks: Principles, mechanisms, and architectures
Stephen Grossberg · 1988
Cited alongside, same era.
When will machines learn?
Douglas B. Lenat · 1988
Cited alongside, same era.
Neural populations revealed
Terrence J Sejnowski · 1988
Cited alongside, same era.
Anatomy of a cortical simulator
Rajagopal Ananthanarayanan and Dharmendra S. Modha · 2007
Later among the works it cites.
Sal: An explicitly pluralistic cognitive architecture
David J Jilk, Christian Lebiere, Randall C O’Reilly, and John R Anderson · 2008
Later among the works it cites.
A world survey of artificial brain projects, part i: Large-scale brain simulations
Hugo de Garis, Chen Shuo, Ben Goertzel, and Lian Ruiting · 2010
Later among the works it cites.
A world survey of artificial brain projects, part ii: Biologically inspired cognitive architectures
Ben Goertzel, Ruiting Lian, Itamar Arel, Hugo de Garis, and Shuo Chen · 2010
Later among the works it cites.
Thinking, fast and slow
Daniel Kahneman · 2011
Later among the works it cites.
A large-scale model of the functioning brain
Chris Eliasmith, Terrence C. Stewart, Xuan Choo, Trevor Bekolay, Travis DeWolf, Yichuan Tang, and Daniel Rasmussen · 2012
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
TJ Sejnowski, C Koch, and PS Churchland · 1988
Cited alongside, same era.
On the proper treatment of connectionism
Paul Smolensky · 1988
Cited alongside, same era.
Logic and the Complexity of Reasoning
Hector J. Levesque · 1989
Cited alongside, same era.
Institutional ecology, ‘translations’ and boundary objects: Amateurs and professionals in berkeley’s museum of vertebrate zoology, 1907-39
Susan Leigh Star and James R. Griesemer · 1989
Cited alongside, same era.
Artificial Experts: Social Knowledge and Intelligent Machines
H.M. Collins · 1990
Cited alongside, same era.
The symbol grounding problem
Stevan Harnad · 1990
Cited alongside, same era.
Later among the works it cites.
Le bluff technologique
J. Ellul · 2012
Later among the works it cites.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
Later among the works it cites.
The ethics of artificial intelligence
Nick Bostrom and Eliezer Yudkowsky · 2014
Later among the works it cites.
Systematicity in the lexicon : On having your cake and eating it too
Jeffrey L. Elman · 2014
Later among the works it cites.
On our best behaviour
Hector J. Levesque · 2014
Later among the works it cites.
The great ai awakening
Gideon Lewis-Kraus · 2016
Later among the works it cites.
The Mythos of Model Interpretability
Z. C. Lipton · 2016
Later among the works it cites.
Progress and challenges in research on cognitive architectures
Pat Langley · 2017
Later among the works it cites.
Mastering chess and shogi by self-play with a general reinforcement learning algorithm
David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, Timothy P. Lillicrap, Karen Simonyan, and Demis Hassabis · 2017
Later among the works it cites.
An overview of national ai strategies, 2018
Tim Dutton · 2018
Closest in time.
Deep learning: A critical appraisal
Gary Marcus · 2018
Closest in time.
Theoretical impediments to machine learning with seven sparks from the causal revolution
Judea Pearl · 2018
Closest in time.
The Deep Learning Revolution
Terrence Joseph Sejnowski · 2018
Closest in time.