--- title: "AI, Turing test, CSP examples" subject: "Artificial Intelligence" chapter: 1 key: "semester_6/artificial_intelligence:turing-test-pass-csp-examples" source: https://www.bctengineer.com/q/semester_6/artificial_intelligence/turing-test-pass-csp-examples site: BCT Engineering --- # AI, Turing test, CSP examples Artificial Intelligence · Chapter 1: Introduction - Asked in: 2070 Bhadra, 2+5+1 marks - Video: [Artificial intelligence | Turing Test](https://www.youtube.com/watch?v=dP3r4mme_vk) — R Udeshi's Lab - Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14 - Page: https://www.bctengineer.com/q/semester_6/artificial_intelligence/turing-test-pass-csp-examples - Whole chapter: https://www.bctengineer.com/md/semester_6/artificial_intelligence/chapter-1 ## Question Define AI. When is a machine said to have passed the Turing test? Give any two examples of constraint satisfaction problem. ## Short answer AI is the branch of computer science making computers perform tasks requiring human intelligence. A machine passes the Turing Test when a human interrogator, after text conversation for a fixed time, cannot reliably distinguish it from a human (identifies it no better than chance). Two CSP examples: map coloring (variables=regions, domain=colors, constraint=adjacent regions different colors) and cryptarithmetic puzzle SEND+MORE=MONEY (variables=letters, domain=digits 0-9, constraints=unique digits, leading non-zero, correct addition). ## Answer #### Definition of AI **Artificial Intelligence** is the branch of computer science that studies how to make computers perform tasks that require human intelligence, such as learning, reasoning, problem solving, perception and language understanding. #### When has a machine passed the Turing Test? In the Turing Test (Alan Turing, 1950), a human interrogator talks through text with a hidden human and a hidden machine. A machine is said to have **passed the test when the interrogator, after asking questions for a fixed time, cannot reliably distinguish the machine's answers from the human's**, that is, the interrogator identifies the machine correctly no better than chance (Turing predicted that by about 2000 a machine would fool an average interrogator at least 30% of the time after five minutes). To pass, the machine needs natural language processing, knowledge representation, automated reasoning and machine learning. #### Two examples of constraint satisfaction problems (CSP) A CSP has variables, domains and constraints; a solution assigns a value to every variable so all constraints hold. 1. **Map colouring:** Colour the regions of a map (e.g. provinces of Nepal) with 3 colours so that no two adjacent regions have the same colour. - Variables: regions; Domain: {Red, Green, Blue}; Constraint: adjacent regions have different colours. 2. **Cryptarithmetic puzzle** (e.g. SEND + MORE = MONEY): Variables: letters; Domain: digits 0-9; Constraints: all letters get different digits, the leading letters are non-zero, and the addition is correct. Other examples: 8-queens, Sudoku, timetable scheduling. ## Check yourself The answer's key points as multiple-choice questions, with the correct option and why. 1. When is a machine said to have passed the Turing test? A. When it answers all questions correctly B. When it responds in under a second C. When the interrogator cannot reliably distinguish its answers from a human's D. When the human judge leaves Answer: C. It passes when the interrogator identifies it no better than chance. (Key point: Passing the Turing Test) 2. What does a CSP consist of? A. States, goals and heuristics only B. Rules and facts only C. Inputs and outputs only D. Variables, domains and constraints Answer: D. A CSP has variables, a domain for each, and constraints; a solution satisfies all of them. (Key point: CSP components) 3. In map colouring with 3 colours, what is the constraint? A. Adjacent regions must have different colours B. All regions must have the same colour C. Each colour used exactly once D. Regions must be coloured red first Answer: A. The constraint is that neighbouring regions get different colours. (Key point: Map colouring constraint) 4. Which is a constraint in SEND + MORE = MONEY? A. Letters may share digits B. All letters get different digits and leading letters are non-zero C. Domain is 1-5 D. No carries allowed Answer: B. Letters take different digits, leading letters are non-zero and the addition must be correct. (Key point: Cryptarithmetic constraints) ## Related in Artificial Intelligence - [Define AI and the Turing test](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Awhat-is-ai-turing-test) — Artificial Intelligence, chapter 1 - [AI, Turing test importance, applications](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Aai-turing-test-importance-applications) — Artificial Intelligence, chapter 1 - [CSP and SWIM+WEAR=RELAX](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Acsp-swim-wear-relax) — Artificial Intelligence, chapter 2 - [Does passing Turing test show intelligence](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Aturing-test-shows-intelligence) — Artificial Intelligence, chapter 1, asked 2× - [CSP and SEND+MORE=MONEY](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Acsp-send-more-money) — Artificial Intelligence, chapter 2 ## Related in other subjects - [Define multitape Turing machine](https://www.bctengineer.com/question.md?key=semester_3%2Ftheory_of_computation%3Atm-multitape-define) — Theory of Computation, chapter 4 - [What is a Turing machine; its operation](https://www.bctengineer.com/question.md?key=semester_3%2Ftheory_of_computation%3Atm-define-operation) — Theory of Computation, chapter 4 - [How a universal Turing machine works](https://www.bctengineer.com/question.md?key=semester_3%2Ftheory_of_computation%3Auniversal-tm-example) — Theory of Computation, chapter 5 - [Resection, two point problem, intersection](https://www.bctengineer.com/question.md?key=semester_4%2Fsurveying_ii%3Aresection-two-point-problem-ab-p) — Surveying II, chapter 5