Créer une présentation
Télécharger la présentation

Télécharger la présentation
## Artificial Intelligence

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -

**Artificial Intelligence**What is AI? Issues in AI**An Overview**- AI is a science of making intelligent machines - Intelligence is a type of computation: What is a computation? Turing Machines - How do we know if a machine is intelligent or not? Turing Test**1. What is AI?**• Artificial intelligence is the science and engineering of making computer programs that exhibit characteristics of human intelligence. • Scientific aim: To understand the requirements for and mechanisms of human, animal, machine, robotic intelligence • Engineering aim: To apply such knowledge in building useful artifacts (machines & robots) capable to do things done by humans or animals**What is intelligence?**- Intelligence is the computational part of the ability to solve problems and achieve goals in the world in an efficientmanner (McCarthy) - ‘Computational part .. to do … efficiently’ Algorithm (e.g.) Tower of Hanoi Problem: Tic-tac-toe: Chess: No. of all possible board states: 10120!! - Combinatorial explosion problem - Blind search – intractable**Branches of AI**Knowledge representation • Processing information about and representing facts about the world in some abstract way Pattern recognition • Extracting knowledge from images (e.g., letters, face, X-ray data, satellite photos) Reasoning and inference • Deriving conclusions from premises or incomplete observations (e.g., logical deduction, math theorem proving, medical diagnosis, stock market/weather forecasting) Machine learning • Improving performance from experience (e.g., rule induction & adaptive modification) Planning • Planning a complex sequence of actions (e.g., playing chess) Natural language processing • Production and interpretation of spoken and written language**Pattern recognition**• Knowledge representation • Reasoning & inference • Machine learning**Applications of AI**Computer vision - IRIS (biometric identification device), detection of forgeries, chip inspection Expert systems • MYCIN (medical diagnosis), HYPO (legal reasoning), auto pilot, intelligent tutoring system Game playing • IBMS’ Deep Blue (search 2m positions per sec) Speech recognition - Dragon Naturally Speaking Robotics - robot moles in Mars exploration**Dartmouth Workshop (1956)**- Summer workshop that officially launched the field known as ‘Artificial Intelligence’ (named by McCarthy) - Participants included: McCarthy (Stanford), Minsky (MIT), Shannon (Lucent), Newell (CMU), Simon (CMU) General Problem Solver (GPS) (Newell & Simon, 1960’s) - Landmark computer program that solves simple problems/puzzles (e.g., Tower of Hanoi) and even comes up with proofs for mathematical theorems - Based on a general problem solving strategy called the ‘mean-ends analysis’ (work backward from the goal to decide on what action(s) will help you achieve in which goals are decomposed into subgoals in a recursive fashion)**Weak AI vs Strong AI**in the Study of Mind (Searl 1980) Weak AI: - “The principal value of the computer in the study of mind is that it gives us a very powerful tool.” Strong AI: - “An appropriately programmed computer literally has cognitive states and therefore explains how the human mind works.”**2. Issues in AI**Issue #1: What is a computation?**Turing Machines (Turing, 1937)**- A Turing Machine, an idealized, mathematical abstraction of a digital computer, consists of (1) 1-dim tape of cells of unlimited length (written on each cell is a symbol from finite alphabet) (2) read/write head (3) control (action) table or program**Control program:**- State of head: {S1, S2, S3} - Binary alphabet on tape: {0,1} - Movement of head: {Left, Right}**A Turing machine that computes:**“2 x 4 = 8”**(Turing’s) Definition of computation**- “A function is said to be computable if it can be implemented on a Turing Machine.” - Such functions are called Turing computable functions (e.g., f(x) = 0; natural log e; +/x; if-then) • Roughly speaking, a function or task is computable if its solution can be found in “finite” time (or polynomial time). • A problem in which the time required to solve grows exponentially as the problem size grows said to be uncomputable (i.e., unsolvable), thereby requiring “infinite” time to solve NP-hard problem (e.g., Traveling Salesman Problem)**Traveling Salesman Problem**16-city problem A candidate solution**Universal (Turing) Machine**- Turing also showed that it is possible to design a single Turing machine that can simulate any Turing machine. Such a machine is called a Universal Turing Machine Church-Turing Thesis: In essence, “A Universal Turing Machine can compute any non-NP-hard problem.” (e.g.) - Programmable computers (PC, MaC) von Neumann Machine - program – control/action table unit - CPU – read/write head unit - RAM - tape - DNA (biological computation device)**Issue #2:**How do we know if a machine is intelligent or not?**Turing Test (Turing, 1951)**- First attempt to define an operational definition of intelligence - Turing defined intelligent behavior as the ability to exhibit human-likeperformance, sufficient to fool an interrogator in an “imitation game”**Can the Turing test be a definition of intelligence?!%**1. A computer may pass the test but without ‘real’ understanding of the conversation that took place (e.g., Searl’s Chinese Room) 2. Many ‘real’ human beings might fail the test. 3. A computer often exhibits intelligence without being a conversational partner (e.g., autopilot)**Chinese Room (Searle, 1980)**- Thought experiment developed as an attack on the Turing Test (againt Strong AI) - Showed that in theory, it is possible to create a system that exhibits intelligent output without understanding (i.e., in the absence of mind), thus passing the Turing test - Would it be practically possible to build such a system? Why or why not?