context LinesVisible inv:
ViewPort : viewContents->size() =
ViewPort : height.min(FileManager : document->size())
context LinesVisible inv:
let topLineNumber = ScrollBar : handlePosition *
FileManager : document->size()
in ViewPort : viewContents = FileManager : document->
subsequence(topLineNumber, topLineNumber + ViewPort: viewContents->size() - 1)
GUI toolkit(library) for textBrowser
-some way to access the file’s contents
-provide a module that can retrieve a limited length, consecutive subsequence of the file’s lines.
-need to be able to display the textual content graphically
-need to give the user some way to access different parts of the file
-three candidate structural elements
-behavior of the TextBrowser
-how the user will use the intended solution
Basic Concept: Why this application exist?
– move handle
– change window(ViewPort) size
– UML class-model diagram
– rectangle for classes
– Each rectangle is divided vertically
– Lines between the components denote relationships
– comprise those actions that the user can undertake to interact with the TextBrowser
“Having employed dozens of designers, I’ve never once taken into account a candidate’s academic qualification. I might take into account with design college, but I’m not swayed by the quality of degree.. I just know that too many good designers achieved poor grades at design school and it is always worth looking beyond academic marks.”
Definition of Scripts
A causally coherent set of events.
1. Each event sets off, or causes, the next event.
2. The causal connections between events make sense.
3. The parts are actions or scenes in the world.
track: formal dining
props: tables, menu, check, money, F = food, P = place
roles: S = customer, W = waiter, C = cook, M = cashier, O = owner
entry: S is hungry, S has money
result: S has less money, O has more money, S is not hungry, S is pleased
David went to the meeting with Ashok by car.
verb : go
agent : David
coagent : Ashok
destination : meeting
conveyance : car
Preposition, Themantic Roles
by | agent, conveyance, location
for | beneficiary, duration
from | source
to | destination
with | coagent, instrument
That was written by Ashok.
David went to New York by train
David stood by the statue.
Why do we need formal logic?
Soundness: Only valid conclusions can be proven.
Completeness: All valid conclusions can be proven.
Vertebrate -> Bird -> Eagle, Bluebird, Penguin
If an animal has feathers, then it is a bird.
If an animal lays eggs and it files, then it is a bird.
Ashok ate a frog.
object: a frog
David ate a pizza at home:
object: a pizza
Angela ate lasagna with her dad last night at Olive Garden.
subject : Angela
object : lasagna
location : Olive Garden
time : night
object-alive : false
object-is : in-subject
subject-mood : happy
Low Level <-> High Level
Hardware/Implementation Level(e.g. a brain, transister), Algrithm/Symbol Level(e.g. means-ends analysis, semantic networks), Task/Knowledge Level(e.g. selecting a pitch, playing baseball)
The layers of Watson: the physical computer searching and decision-making answering the inputted clue
Assumptions of a Cognitive Architecture
– Rich, complex envrionment
– Significant knowledge
– Symbols and abstractions
– Flexible and function of the environment
Architecture + Content = Behavior
Function for cognitive architectures: f:P* -> A
Percepts -> Action
Procedural, Semantic, Episodic
-> Working Memory
x -> x :unchanged
y -> y :expanded
z -> z :deleted
structurally: directional links
semantically: application specific labels
Guards and prisonaers
5point for unchanged, 4 for reflected, 3 for rotated, 2 for scaled, 1 for deleted, 0 for shape changed
-intelligent agents have limited resources
-computation is local, but problems have global constraints
-logic is deductive, but many problems are not
-The world is dynamic, but knowledge is limited
-Problem solving, reasoning, and learning are complex, but explanation and justification are even more complex
Characteristics of AI Agents
-Agent have limited computing power
-Agent have limited sensors
-Agent have limited attention
-Computational logic is fundamentally deductive
-AI agents’ knowledge is incomplete relative to the world
Deliberation:Reasoning, Learning, Memory
machine learning, semantic web, airplane autopilot, improvisational robots