Topic 5 - Symbolic Systems Flashcards
1
Q
Four Properties
A
- Representations
- Transformations
- Serial Processing
- Sense-think-act
2
Q
Eliza
A
- Rogerian Therapy dictates that people can’t be told how to solve their problems, they need to discover it themselves
- Very simple chatbot called Eliza basically repeats things back to the patient
- Representations: User input strings
- Transformations: Predefined responses to specific inputs
- Serial Processing: Running the program
- Sense-think-act: Input problem, process, output therapy
3
Q
Shrdlu
A
- Chatbot that can manipulate objects in a 3D virtual environment
- Representations: User input, blocks in world
- Transformations: Responses, rules of how blocks can be manipulated
- Serial Processing: Running the program:
- Sense-think-act: Input problem, figure out how to solve it, move blocks accordingly
4
Q
Soar
A
- Problem being solved: Move train engines and flatcars from one configuration to another along a split track
- Representations: Problem spaces with different problem states and operators (actions)
- Rules: When there’s an impasse, a new “selection” problem space is created with the goal of breaking the tie, which uses more switch spaces recursively
- How Soar learns: When an impasse is resolved, Soar stores the configuration of states and moves and the state they lead to in chunks
- How many times does Dr. Rosenbloom say Chunk: 10
5
Q
Mycin
A
- Blood disorder diagnosis bot
- Eliminates possible diagnoses until it is reasonable certain of a particular result
- Outperformed Stanford med students and faculty, but isn’t used for legal/ethical reasons
- Can’t diagnose anything that isn’t a blood disease
6
Q
WATSON
A
- IBM bot that won jeopardy
- Weighs evidence to answer questions based on a lot of different factors
7
Q
Pedro
A
- Lego MINDStorms bot that would move in response to sounds or proximities
- Representations: Sensory data
- Transformations: Specific instructions for when sensory data is acquired (move forward when sound is loud, etc)
8
Q
Marr’s Three Levels
A
- Explanation has three levels: Task description (eg math), algorithm description (eg computer program), physical description (eg transistors and bits)
- We won’t be truly “done” cognitive science until we understand all three for our brains
9
Q
Edge Detection
A
- Detecting boundaries between objects is hard
- Difference of Gaussian’s Filter (algorithm level)
- There are cells in the LGN in our brains that seem to more-or-less do this (physical level)
10
Q
Neural Network Edge Detection
A
- Neurons get inputs from other neurons, some of which repress other signals
- If there’s a strong reaction in the middle and a weaker connection to the sides, then we find an edge
- Try using simulated neurons to figure out how the brain works