Artificial Intelligence: Critical Concepts, Volume 2Ronald Chrisley, Sander Begeer |
Contents
Computing machinery and intelligence | 19 |
A proposal for the Dartmouth Summer Research Project | 44 |
Report on a general problemsolving program | 69 |
The simulation of psychological processes | 88 |
Steps toward artificial intelligence | 102 |
Symbols and search | 155 |
Artificial intelligence where are we? | 182 |
Excerpts from The Society of Mind | 223 |
PART II | 345 |
On Alan Turings anticipation of connectionism | 381 |
A probabilistic model for information storage | 398 |
A paradigm for learning | 428 |
Horses of a different color? | 445 |
Waking up from the Boolean Dream or subcognition | 465 |
The prospects for building truly intelligent machines | 523 |
Connectionism and the foundations of AI | 541 |
Mathematical logic in artificial intelligence | 248 |
On the thresholds of knowledge | 298 |
Logical vs analogical or symbolic vs connectionist | 562 |
Other editions - View all
Artificial Intelligence: Critical Concepts, Volume 4 Ronald Chrisley,Sander Begeer Limited preview - 2000 |
Artificial Intelligence: Critical Concepts, Volume 1 Ronald Chrisley,Sander Begeer Limited preview - 2000 |
Artificial Intelligence: Critical Concepts, Volume 3 Ronald Chrisley,Sander Begeer Limited preview - 2000 |
Common terms and phrases
A-units abstract activity advice taker Alan Newell analogy apply architecture artificial intelligence B-type behavior brain C. E. Shannon Cambridge chunks cognitive cognitive science complex concepts connectionism connectionist connections demons described developed digital computer discussion domain Dreyfus brothers environment example experience expert systems formal functions goal GOFAI heuristic holism human hypothesis ideas input kind knowledge language learning logic machine learning mathematical McCarthy McCulloch and Pitts means mechanisms memory methods mind Minsky networks neural neurons Newell nodes objects operator output paradigm parallel pattern perceptron performance philosophical physical possible problem space problem-solving procedure processes psychological question random reasoning represent representations response Rosenblatt rules Rumelhart semantic sense Simon simple simulate Soar Society of Mind solution solving source-set stimuli structure subdemons subgoal subsymbolic symbol systems task theory things tion Turing Turing machine Turing's understanding units unorganised machines y-system York