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Papers
Papers that changed AI, with a plain-language explainer for each.
Total 199
- 1992
Q-learning
Machine Learning
A 1992 technical note by Watkins and Dayan that set out Q-learning, an incremental and computationally light way for an agent to learn optimal action values, and proved it converges to the optimum with probability 1.
- 1990
Elephants Don't Play Chess
Rodney Brooks's 1990 paper argued for building artificial intelligence from the ground up, with ongoing physical interaction with the environment as the main constraint on design, rather than through the abstract manipulation of symbols that had dominated the field for roughly thirty years.
- 1989
Backpropagation Applied to Handwritten Zip Code Recognition
Neural Computation
In 1989 LeCun and colleagues at AT&T Bell Laboratories trained a convolutional network with backpropagation to read handwritten zip-code digits from U.S. mail, reaching 5.0% test error. The work showed that the convolutional design could be learned end to end on a real task.
- 1988
Learning to predict by the methods of temporal differences
Machine Learning
Richard Sutton's 1988 paper introduced temporal-difference learning, a family of incremental prediction methods that assign credit from changes between successive predictions and are shown to be more economical and accurate than conventional supervised approaches on most prediction problems.
- 1988
ALVINN: An Autonomous Land Vehicle in a Neural Network
ANIPS11
A 3-layer back-propagation network that takes camera and laser range finder images and outputs the direction to steer, trained on simulated road images and tested on Carnegie Mellon's autonomous navigation test vehicle.
- 1986
Learning representations by back-propagating errors
Nature
In a 1986 Nature paper, Rumelhart, Hinton and Williams showed that backpropagation lets hidden units in a multilayer network learn useful internal features of a task. The method is standard in most neural networks today.
- 1985
A Learning Algorithm for Boltzmann Machines
Cognitive Science 9
A 1985 Cognitive Science paper by Ackley, Hinton and Sejnowski that presents a general learning rule for connectionist networks and reports simple examples of efficient internal representations.
- 1982
Neural networks and physical systems with emergent collective computational abilities
PNAS
A 1982 paper by John J. Hopfield showing that large networks of simple neuron-like units can collectively store and recall memories. It became known as the Hopfield network, and the work was recognised by the 2024 Nobel Prize in Physics.
- 1982
Neural networks and physical systems with emergent collective computational abilities
PNAS
A 1982 paper by John J. Hopfield arguing that useful computation can emerge as a collective property of many simple, equivalent units, and describing a model whose collective behaviour gives content-addressable memory, generalisation and error correction.
- 1969
Perceptrons: An Introduction to Computational Geometry
A 1969 book by Marvin Minsky and Seymour Papert that proved mathematical limits on what single-layer perceptrons can compute — notably that they cannot compute parity or connectedness — and has long been credited with steering research away from neural networks.
- 1966
ELIZA - A Computer Program for the Study of Natural Language Communication Between Man and Machine
Communications of the ACM 9(1)
A January 1966 paper by Joseph Weizenbaum presenting ELIZA, a program on MIT's MAC time-sharing system that used keyword-triggered decomposition and reassembly rules to enable certain natural-language conversations between people and computers.
- 1961
Steps Toward Artificial Intelligence
Proceedings of the IRE 49(1)
Marvin Minsky's 1961 survey in Proceedings of the IRE organized heuristic programming into five problem areas — search, pattern recognition, learning, planning and induction — and argued that machines would need to build models of their environments.
- 1959
Some Studies in Machine Learning Using the Game of Checkers
IJRD
A. L. Samuel's 1959 paper reporting experiments in which a checkers program, given only the rules of the game and an imperfect set of parameters, learned in 8 to 10 hours of playing time to beat the person who wrote it.
- 1959
Programs with Common Sense
PSMTPNPL
John McCarthy's 1959 paper proposing the advice taker, a program that would solve problems by manipulating sentences in formal languages and act when it deduced an imperative — an early statement of logical AI.
- 1958
The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain
Psychological Review
In 1958 Frank Rosenblatt described the perceptron, a model whose connection strengths change with training so that it learns to classify stimuli by trial and error. It became the starting point for trainable neural networks.
- 1950
Computing Machinery and Intelligence
Mind
In 1950 Alan Turing replaced the question "Can machines think?" with the imitation game, now called the Turing test, and answered the main objections to machine intelligence one by one.
- 1948
A Mathematical Theory of Communication
Bell System Technical Journal 27
C. E. Shannon's 1948 paper set out a mathematical framework for communication, defining information in bits, channel capacity, and entropy, and treating messages statistically while setting aside semantic meaning.
- 1943
A Logical Calculus of the Ideas Immanent in Nervous Activity
Bull. Math. Biophys.
In 1943 Warren McCulloch and Walter Pitts described a simplified model of a neuron and showed that networks of such units can carry out logical reasoning, an early link between brain models and computation.
- 1936
On Computable Numbers, with an Application to the Entscheidungsproblem
Proc. London Math. Soc.
Alan Turing's 1936 paper defined computable numbers through an abstract machine, now called the Turing machine, and showed that no general method can decide whether any given mathematical statement is provable.