From the Wikipedia:
"The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind is a 2006 book by cognitive scientist Marvin Minsky that elaborates and expands on Minsky's ideas as presented in his earlier book Society of Mind.
Minsky argues that emotions are different ways to think that our mind uses to increase our intelligence. He challenges the distinction between emotions and other kinds of thinking. His main argument is that emotions are "ways to think" for different "problem types" that exist in the world, and that the brain has rule-based mechanisms (selectors) that turn on emotions to deal with various problems. The book reviews the accomplishments of AI, why modelling an AI is difficult in terms of replicating the behaviors of humans, if and how AIs think, and in what manner they might experience struggles and pleasures." (https://en.wikipedia.org/wiki/The_Emotion_Machine)
Compiled by Nathan Slater:
2.17. Why We Will Need Them
9.14. Students who hear that "GOFAI" failed should learn more about AI's history!
- 1957 Arthur Samuel's machine plays master-level Checkers.
- 1957 NEwell, Shadw and Simon. Proving logical theorems.
- 1960 Herbert Gelernter: Proving theorems in Geometry
- 1960 James Slagle: Symbolic Integral Calculus
- 1963 Lawrence G. Roberts: 3-D Visual Perception
- 1964 Thomas G. Evans: Solving Geometry Analogy problems
- 1965 Daniel Bobrow: Solving word problems in Algebra
- 1969 Engelmann, Martin and Moses: the MACSYMA project.
- 1969 Minsky-Papert-Winston robot builds structures
- 1970 Terry Winograd: A program understands sentences
- 1972 Sussman: A program recognizes some bugs in programs
- 1974 Eugene Charniak: A program understands some stories.
Computers and thought
Terry Winograd 1970 Controlling a Robot with Verbal Commands
"is the red block taller than the green block?" answered
Book on AI. Patrick Winston Jerry Sussman - Fixing of Bugs - 1972
29.40. Fads in AI
- Reinforcement Learning = Deficient in Credit Assignment
- Rule-Based Systems = Limited Representation
- Neural Networks = Opague to Reflective Thinking
- Statistical Inference = Fails to use Causal Reasoning
- Formal Logic = Cannot exploit analogies
- Genetic Programs = Fail to remember the causes of failures
- Insect-like Robots = These projects just re-create previous ones.
- Baby Machines = All have failed to develop high level thinking
But each method works only in certain domains. We need to know both when each method works and why it fails.
30 & 31. Jerry Sussman and Hal Ablenson
One program to use an AI working to solve the problem.
43.17. A "Critic-Selector" Theory of Brain
Suppose you fail to achieve a goal or your thinking gets stuck in some other way. Then your brain uses special machinery to (1) diagnose what went wrong and (2) activate some more appropriate Way to Think.
Recognize a Problem-Type >> Activate a "Way to Think"
CRITICS / SELECTORS
If a problem seems familier, try reasoning by Analogy. If it seems unfamilier, change how your describing it. If it still seems too difficult, divide it into several parts. If a problem is too complex, replace it by a simpler one. If your methods do not work, ask someone else for help.
51.23. Old vs. new views of emotion
Old view of Emotion: Emotional states augment our mind the way artists add colors to black and white drawings.
New view of Emotions : Each emotional state suppresses certain features of regular thinking.
CSAIL. Marvin Minsky. Emotion Machine
Read 'Emotion Machine' by Marvin Minsky
Watch the video linked below as you read the notes.
Notes are based on this video