A History of Artificial Intelligence

This is heavily biased guide to the historical development of artificial intelligence.

Timeline

1940s

1. 1943, December : A LOGICAL CALCULUS OF THE IDEAS IMMANENT IN NERVOUS ACTIVITY
   • summary : First conceptual and computational model for neural networks
   • authors : McCulloch and Pitts
2. 1948, July : A Mathematical Theory of Communication
   • summary : Creation of the Field of Information Theory
   • authors : Claude E. Shannon
   • references :
     • Wikipedia
3. 1949 : The Organization of Behavior: A Neuropsychological Theory
   • summary : The introduction of Hebbian learning, a foundational concept in neural network theory.
   • authors : D. O. Hebb
   • references :
     • Wikipedia

1950s

1. 1950, March : Programming a Computer for Playing Chess
   • summary : A test case for the coming generation of artificial intelligence programs.
   • authors : Claude E. Shannon
2. 1950, October : Computing Machinery and Intelligence
   • summary : Proposal of the Turing Test, a model for determining whether a machine has human level intelligence
   • authors : Alan Turing
3. 1955, August : A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence
   • summary : The founding document for the field of AI
   • authors : John McCarthy, Marvin Minsky, Nathaniel Rochester, Claude E. Shannon
4. 1956, September : The logic theory machine--A complex information processing system
   • summary : First automated reasoning program
   • authors : A. Newell, H. Simon & C. Shaw
5. 1959 Programs with Common Sense
   • summary : Common Sense Reasoning
   • authors : John McCarthy
6. 1959 : GPS, a Program that Simulates Human Thought
   • summary : Described the General Problem Solver (GPS), an early AI program designed to mimic human problem-solving.
   • authors : H. Newell, J.C. Shaw, and H.A. Simon
7. 1959, July : Some Studies in Machine Learning Using the Game of Checkers
   • summary : Described one of the first successful self-learning programs, applying machine learning to checkers.
   • authors : Arthur Samuel

1960s

1. 1965, June : Fuzzy Sets
   • summary : Introduction of Fuzzy Sets
   • authors : L.A. Zadeh
2. 1968, July : A Formal Basis for the Heuristic Determination of Minimum Cost Paths
   • summary : Introduced the A* search algorithm, a cornerstone in pathfinding and graph traversal algorithms in AI.
   • authors : Peter E. Hart, Nils J. Nilsson, Bertram Raphael
3. 1969 : Perceptrons: An Introduction to Computational Geometry
   • summary : This book critically analyzed the capabilities and limits of perceptrons, influencing the direction of AI research and leading to the first AI winter.
   • authors : Marvin Minsky, Seymour Papert

1970s

1980s

1. 1984, November : A Theory of the Learnable
   • summary : laid the foundation for computational learning theory, introducing the concept of Probably Approximately Correct (PAC) learning.
   • authors : Leslie Valiant
2. 1986, March : Induction of decision trees
   • summary : In
   • authors : J. R. Quinlan
3. 1986, October : Learning representations by back-propagating errors
   • summary : This paper introduced the backpropagation algorithm, a cornerstone in training neural networks.
   • authors : David E. Rumelhart, Geoffrey E. Hinton & Ronald J. Williams

1990s

1. 1995, September : Support-vector networks
   • summary : Support Vector Machines
   • authors : Corinna Cortes & Vladimir Vapnik
2. 1997, November : Long Short-Term Memory
   • summary : introduction of LSTMs
   • authors : Sepp Hochreiter & Jürgen Schmidhuber