PHI 013G

SHRDLU: Designed as a piece of ___

- AI - It's a 3D system that can do things/perform tasks - simulates robot arm which can move a set of shapes - Humans engage with the computer ex/ ask questions, issues commands - SHRDLU uses syntax, semantics (bc people must give it commands in order for it to work, so it can be seen as ("understanding"), and facts about the blocks to perform tasks - Restricted domain- hence name of micro-world (doesn't give insight to real world) - LIMITATIONS: fixed representation, no semantic depth, just carries out process (Searle says this in general about computers) - "It knows what it owns, but it doesn't know what it is like to own something" (pg 150) ...also Lady Lovelace's argument from the Turing section - Application of micro-worlds: computer vision

Counterargument to Turing test: consciousness

- Argument - To be sure that machines think is to be the machine - Turing's Response: this is the solipsist's point of view: only way to know that a human is thinking is to be the human, and we can't be other people so this is not enough - He's saying that we might each have just as much reason to suppose that machines think as we have reason to suppose that other people think

argument to informality and counterargument

- Argument: It is not possible to produce a set of rules for every moment a man accomplishes a task, if he did have rules, he would be like a computer, but he isn't, so they're not alike - Turing's Response: Just because we don't follow rules of behavior, doesn't mean we don't follow rules of conduct just like a computer!

Counterargument to Turing test: Lady Lovelace

- Argument: Computers lack originality (ex/ thoughts), and are therefore not intelligent - Turing's Response: How do you know if the work of a human is truly original, let alone a computer's?

Counterargument to Turing test: Disabilities

- Argument: computers lack feature x, and x is important and necessary*** for intelligence, so computers are therefore not intelligent - Examples of x: > "Be the subject of its own thoughts" > "Make mistakes" > "Do something really new" - Turing's Response: These "disabilities" are irrelevant bc/ it is an unfair comparison. If you compare a race between man and the plane, plane will obviously win w/ respect to speed being an example of feature x

Churchlands' 3 axioms

- Axiom 1: electricity and magnetism are forces - Axiom 2: the essential property of light is luminance - Axiom 3: forces by themselves are neither constituted of nor sufficient for light

conclusions of Turing machine

- Better representation of our brain processing - Read/write machine; can move left and right

'Turing: Can Machines Think' basic argument

- Brains are like computers (computationalist view) - In the brain we have a CPU that is distinct/separate from where the memory is stored AKA Von Neumann Architecture (Strong AI according to Searle) - Brains are really just a bunch of algorithms that analyze and make decisions (outputs)

Counterargument to Turing test: informality

- Definitive rules of conduct where man has to regulate themselves, they would be no better than a machine, however if there are no such rules, man cannot be machines

Counterargument to Turing test: continuity

- Digital like pixels: distance and well defined, discrete (Discrete-state system, VN architecture, Turing machines, UTM, etc.) - Analogue: not discrete/all smeared states like a record (human brain works this way) - Argument: Humans are made of a continuous system, not a discrete system where everything is done serially, human brains compute in parallel. Therefore, computers can't be intelligent because parallel machines can compute serially but not vice versa (searle article). - Turing's Response: The imitation game would in no way be a continuous system, but if played properly, it wouldn't even matter because nobody *should* tell the difference between the computer and the human (that's the point of the imitation game)

Neural Networks

- Dynamic: can change over time - Can change through feedback

Frame defintion

- Frame definition: an information structure for stereotyped situations - Ex: when you go to a restaurant you know you have to see if you need to wait to be seated, wait for a menu, decide on what to drink, etc. - Need to identify base things that are a part of stereotyped situations

Paul Churchland and the Neural Nets

- Highly Simplified model networks have been useful in suggesting how real neural networks might work and in revealing the computational properties of parallel architectures. - This network is a device for transforming any one of great many possible input vectors (activation patterns) into a uniquely corresponding output vector It is a device for computing a specific function - Exactly which function it computes is fixed by the global configuration of its synaptic weights

Dorsey says this structure *should* be applied to every argument

- Humans are intelligent have feature X - Computers lack feature X - Feature X is necessary condition for intelligence - Computers are not intelligent

Von Neumann architecture

- Is a theoretical design for a stored program computer that serves as the basis for almost all modern computers. - A von Neumann machine consists of a central processor with an arithmetic/logic unit and a control unit, a memory, mass storage, and input and output. - Processing of symbols and expressions are processed by a distinct processor. ( in contrast to neural networks who do not have an independent processor, they process in parallel)

Physical symbol system hypothesis

- It is a position in the philosophy of artificial intelligence formulated by Allen Newell and Herbert A. Simon. - A physical system has necessary and sufficient means for general intelligence. > implies both that human thinking is a kind of symbol manipulation (because a symbol system is necessary for intelligence) and that machines can be intelligent (because a symbol system is sufficient for intelligence)

what is 'necessary' in terms of PSS

- Necessary: any system that exhibits general intelligence will prove upon analysis to be a PSS - Therefore, humans must be PSS! - Part of a sufficiency test for intelligent action

Computationalism vs. Connectionism

- Neural nets can't be PSS because they have parallel processing (i.e., they don't have Von Neumann architecture) - Homunculus problem: if brains are neural nets - Thinker within the thinker's mind repetitive pattern, a reason why computationalist example of "what if there is a thinker in the brain doing the thinking" doesn't work

a physical system

- Obeys laws of physics, realized by engineered systems made of engineered components - Not restricted to human symbol systems

definitions - physical -symbol -symbol system

- Physical- clearly obeying laws of physics, realizable by engineered systems made of engineered components - Symbol- An entity, a physical pattern that can occur as a component of another type of entity, not restricted to human symbol systems - Symbol System- a set of entities mentioned above

grammar under LOTH

- Purely formal - How to put PS together to form actual thoughts and not gibberish

Frame problem

- Real AI cannot happen in microworlds- if SHRDLU was put in the real world (or a simulation of the real world), it would have no idea what to do - Frames are supposed to help move from micro-world to real world - When presented with an unfamiliar subject, a computer does not know what information is important and what is unnecessary - While a chatbot or search engine can reasonably function using pure word-to-word textual references, they falter when topics become more specialized; chatbots become incoherent, search engines tend to present only the most popular or obvious information.

Computationalism:

- Strong: humans are Good Old Fashioned PSS. Look at the brain, identify the processor. Memory generates symbol structures in memory then searches it to solve problems. The brain is a PSS and have Von Neumann architecture - Weak: GOF are useful tools for studying humans or human cognition, it is a tool, and does not claim that the brain is a GOF PSS.

'Searle, the Churchlands, and the Chinese Gym' Churchlands' Argument

- The luminous room argument: > Imagine a man waving a magnet in a darkroom. Could waving the magnet around produce light? > Conclusion: Electricity and magnetism are neither constituted of nor sufficient for light

executor of grammar under LOTH

- The thinker - Knows grammar - Purely formal rules

LOTH thought as language as ..?

- Thought as language- language can be combined in multiple ways - Rules are syntactic (Not semantic) - do not have to tell you what components mean

conclusion of FSAs

- Very long, convoluted and taxing - Not a very good model of how our brain processing works - Read only machine- can't write or erase like a Turing Machine - Cannot handle infinite states such as a^n b^n because that would require counting: do not have memory

Parallel systems are described as _____ manipulating symbols according to structure sensitive rules

- not - It's one of the many cognitive skills that a network may or may not learn to display - Rule governed symbol manipulation is not its basic mode of operation

Churchlands' model network over ______ the structure of the brain but it does illustrate several important ideas

- simplifies - Parallel architecture provides a framatic speed advantage over traditional computer - Stores large amounts of information that can be accessed in milliseconds

back propogation

- trial and error format used to correct weights to desired amount - Nodes later in the net can affect nodes earlier in the net - Human brain has back propagation - but it's rare. Most neural networks depend on back propagation but this isn't really how neurons operate

'Fodor & Pylyshyn' What are the two major traditions in theorizing about the mind? (from the reading)

1. Representationalist 2. Eliminitavist

3 laws of informality

1.) Laws of conduct: It seems to run something like this: "If each man had a definite set of rules of conduct by which he regulated his life he would be no better than a machine. But there are no such rules, so men cannot be machines." 2.) Law of behavior: By "laws of behavior" I mean laws of nature/biological as applied to a man's body such as "if you pinch him he will squeak". If we substitute "laws of behavior which regulate his life" for "laws of conduct by which he regulates his life" 3.) Human beings are informal: We have no explicit procedures for the unexpected, only for what is expected

4 steps of FSA

1.) We begin in start state 2.) If the next input character matches the label on the transition from the current state to a new state, go to that new state. 3.) Continue making transitions on each input 4.) If no move is possible, then stop (go to trash state), or if in accepting state, then accept.

3 axioms (actual not examples)

1.) computer programs are formal 2.) human minds have semantic knowledge 3.) syntax does not equal semantics 4.) brains cause minds

Turing Machine

A Turing machine is an idealized computing device consisting of a read/write head (or 'scanner') with a paper tape passing through it. The tape is divided into squares, each square bearing a single symbol--'0' or '1', for example. This tape is the machine's general purpose storage medium, serving both as the vehicle for input and output and as a working memory for storing the results of intermediate steps of the computation.

Physical symbol system (according to Newell and Simon)

A physical symbol system (also called a formal system) takes physical patterns (symbols), combining them into structures (expressions) and manipulating them (using processes) to produce new expressions.

Design Stance

A second method, which involves taking the "design stance", is to attribute functions to the system or its parts and to predict that the system will function properly. We can predict that a jogger's pulse will increase as she heads up the hill because of what we know about exercise and the proper function of the circulatory system. Dennett describes an alarm clock. It's function or design is to wake a person up at a designated time. It has a button for snooze. It is designed to execute a function. (In other words, ignore physical components and just on basis of design, predict that system will behave as it is designed to behave)

Intentional Stance

A third method, which involves taking the "intentional stance", is to attribute beliefs and desires to the person, and then to predict that he will behave rationally, given those beliefs and desires. On Dennett's view, a system with beliefs is a system whose behavior, while complex and difficult to predict when viewed from the physical or the design stance, falls into patterns that may be captured with relative simplicity and substantial if not perfect accuracy by means of the intentional stance. (Figure out what the object's purpose is, what the beliefs and desires it ought to have are with respect to its function in world (ex/ stop sign on the street versus it being washed up on the beach, it was designed for traffic), and predict that it will act to do what it was made to do)

Graceful decay

Although some nodes may be lost overtime, it does not inhibit the overall productivity of the system

Searle's Chinese _____ argument in response to the Chinese Room rework by the Churchlands

Chinese Gym: Searle now imagines he is inside a gym with several other men, none of whom speak Chinese. But they all follow instructions properly, and their responses fool whomever is outside the room into thinking they speak Chinese. This was a response to parallel processing and neural nets argument of the Churchlands

Interpretationism

Choose whether or not to have that belief. In class he discussed what makes a good spouse. It's very subjective because what one characterizes as a good spouse might totally be different from someone else. "all in the eyes of the beholder"

designation

Designation- expression designates an object, if the system can affect the object or behave in ways depending on the object

Turing test was designed to...?

Designed to distinguish AI [Artificial Intelligence] from normal computers

Dreyfus argued that human intelligence and expertise depend primarily on..?

Dreyfus argued that human intelligence and expertise depend primarily on unconscious instincts rather than conscious symbolic manipulation, and that these unconscious skills could never be captured in formal rules.

FSA

Finite state automaton is a simple idealized machine used to recognize patterns within input taken from some character set.

heuristic search

Heuristic search: the solutions to problems are represented as symbol structures. A physical symbol system exercises its intelligence in problem solving by search, i.e., generating and modifying symbol structures until it produces a symbol structure

Turing test design

Imagine you are having a conversation with two people. One is a computer, the other is a human. It is debated as to whether or not you should know one is a computer. Regardless, if the computer carries on the conversation normally like a human, then it passes the Turing Test.

interpretation

Interpretation- given an expression (set of symbols), the system can perform the process

means-ends problems

Means-ends problems - A means-ends problem first determines the goal then steps to achieve that goal. For instance, getting from point a to b using smaller steps to reach that goal. Each step brings you closer to the goal.

Objectivism

Objective facts. In class he discussed it like a virus. Either you have the virus or you don't.

'Dennett and the Intentional Stance' ______ vs _______

Objectivism vs. interpretationism

Physical Stance (also H2O molecule example from class)

One method, which involves taking what Dennett calls the "physical stance", is to apply our knowledge of physical law. We can predict that a diver will trace a roughly parabolic trajectory to the water because we know how objects of approximately that mass and size behave in fall near the surface of the Earth. A water molecule is a physical thing. It is made up of two hydrogens and one oxygen.

Searle's Chinese room explanation

Searle imagines himself alone in a room following a computer program for responding to Chinese characters slipped under the door. Searle understands nothing of Chinese, and yet, by following the program for manipulating symbols and numerals just as a computer does, he produces appropriate strings of Chinese characters that fool those outside into thinking there is a Chinese speaker in the room. The narrow conclusion of the argument is that programming a digital computer may make it appear to understand language but does not produce real understanding (this is the distinction between syntax and semantics). The broader conclusion of the argument is that the theory that human minds are computer-like computational or information processing systems is refuted. Instead minds must result from biological processes; computers can at best simulate these biological processes. The claim is that even if reasonable natural language responses are being generated that are indistinguishable from ones a native Chinese speaker would generate, there is no "understanding" since only meaningless symbols are being manipulated

what is sufficient in terms of PSS

Sufficiency: given that it is necessary for intelligence that the system is a PSS, any PSS can be developed into an intelligent system provided it is of sufficient size.

Water pipe simulation

The brain simulator is simulating the wrong things about the brain- as long as it simulates only the formal structure of the sequence of neuron firings at the synapses, it won't have simulated what matters about the brain: its ability to produce internal states

Turing Machine pt. 2

The input that is inscribed on the tape before the computation starts must consist of a finite number of symbols. However, the tape is of unbounded length. The read/write head is programmable. The Turing machine can read the symbol currently under the head, write a symbol currently under the head, or delete and rewrite if there is already one. Move the tape left or right one square, change state, or halt. A program or 'instruction table' for a Turing machine is a finite collection of instructions, each calling for certain atomic operations to be performed if certain conditions are met.

The job of an FSA

The job of an FSA is to accept or reject an input depending on whether the pattern defined by the FSA occurs in the input in an automated fashion.

Searle and the Chinese room was a counterargument to

Turing test

example of Good old fashioned PSS

Von Neumann architecture: with a distinct memory store and processor. Solves problems by means-ends and search trees.

Feed forward

activation is flowing only forward in the neural net

constituents

basic units of thought

PSS's use ______ search to solve problems

heuristics

LOTH stands for

language of thought hypothesis

heuristics generate ______ via framing

solutions