NET DEC (2021) - BFS

Duration: 2 min

This video lesson is available to enrolled students.

Return to /learn/MPPSC-ASSISTANT-PROFESSOR-COMPUTER-SCIENCE-PAPER-2/current-trends-technologies/search-algorithms/best-first-search/asset-net-dec-2021-bfs after enrolling

Inside: a video lesson and guided study material.

Module outline

  1. About Course: About the Course
  2. Paper 1 | General Studies: State Wise GK
  3. Paper 1 | Information and Communication Technology: Role of Internet and Web Services, Security in Mobile and Wireless Computing
  4. Paper 1 | Current Affairs: GK- Current Affairs
  5. Paper 2 | Discrete Mathematical Structure: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Set Theory, Relations, Functions, Graph Theory, Group Theory, Propositional and Predicate Logic, Probability
  6. Paper 2 | Digital Computer Organization And Architecture: Number System, Number Representation, Sequential Circuits, Combinational Circuit, Basics of COA, Floating Point Rep, Cache Memory Organization, Input Output Organisation, Pipelining, Instr Formats & Modes, Register Transfer and Microoperations, Control Unit Design, Programming the Basic Computer
  7. Paper 2 | C Programming: C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling
  8. Paper 2 | Programming Languages & Object-Oriented Programming Concepts: Java, OOPS with C++, Java Fundamentals, Array, String, IO & References
  9. Paper 2 | Python: Introduction to Python, Tokens, Variables, Data Types, I/O, Operators & Expressions, Control Flow & Looping, Collections & Strings, Functions & Modules, File Handling & Data Analysis
  10. Paper 2 | Data Structure And Algorithms: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing, Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Minimum Spanning Trees, Advanced Algorithms
  11. Paper 2 | Operating System: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Deadlock, Threads & Process Creation, Memory Management, Virtual Memory, Disc Scheduling, File Management, Unix OS
  12. Paper 2 | Theory Of Computation: Introduction to TOC, Deterministic FA (DFA), Non-Deterministic FA, Regular Expressions, Grammar, Regular Language Properties, Moore & Mealy Machines, Pushdown Automata & CFG, Turing Machines, Complexity Theory
  13. Paper 2 | Compiler Design: Intro to Compilers, Lexical Analysis, Grammar & CFG, Syntax Analysis: Top-Down, Syntax Analysis: Bottom-Up, Semantic Analysis & SDT, Intermediate Code Gen, Code Optimization, Run Time Environment
  14. Paper 2 | Database Management System: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, Relational Algebra, SQL, Transaction Management, Concurrency Control, Database Recovery, Database Security & Authorization, Enhanced Data Models
  15. Paper 2 | Computer Network And Information Security: Introduction to CN, Data Communication, Application Layer, Hardware basics, Cyber Threats and Malware Attacks, Network Security, DLL: Access Control, DLL: Flow Control, DLL: Error Control, DLL: Framing, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Net Layer:Routing Protocol, Transport Layer Services, TL: Congestion & UDP
  16. Paper 2 | Software Engineering: Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management
  17. Paper 2 | Current Trends & Technologies: Emerging Tech Trends, Approaches to AI, Search Algorithms, Game Playing, Knowledge Representation, Planning, Multi Agent Systems, Fuzzy Sets, Natural Language Processing, Artificial Neural Networks, Genetic Algorithms, Artificial Intelligence, Data Warehousing & Mining, Electronic Data Interchange and E-Commerce, Terms & Abbreviations
  18. Paper 2 | Full Length Mock Tests:
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

The video presents a GATE NET DEC 2021 question on search algorithms in artificial intelligence, asking which statements are false regarding best-first search, A*, recursive best-first search, and the admissibility of h(n) = 0 for the 8-puzzle. The instructor evaluates each option, noting that statement A is false because best-first search is not guaranteed to be optimal despite often being efficient. Statement B is true, as A* is complete and optimal when h(n) is admissible or consistent. Statement C is false, as recursive best-first search has poor space complexity but efficient time complexity—though the instructor clarifies this is a common misconception. Statement D claims h(n) = 0 is admissible for the 8-puzzle, which is true because it never overestimates the cost to reach the goal. The instructor uses handwritten annotations on a digital whiteboard, highlighting 'h(n)=0 → admissible' and emphasizing that h(n) = 0 is a valid heuristic. The correct answer, as indicated in the question, is 'a) A and D only', but the instructor correctly identifies that both A and D are false, with D being true—indicating a possible error in the provided answer key. The teaching progression focuses on evaluating algorithmic properties such as optimality, completeness, and admissibility through direct analysis of each statement.

Chapters

  1. 0:00 – 1:34 00:00-01:34

    The video presents a GATE exam question (NET DEC 2021) on search algorithms in artificial intelligence, asking which statements are false. The question evaluates four claims: A) Best-first search is not optimal but efficient; B) A* is complete and optimal if h(n) is admissible or consistent; C) Recursive best-first search has good time complexity but poor space complexity; D) h(n) = 0 is an admissible heuristic for the 8-puzzle. The instructor analyzes each option, with handwritten annotations emphasizing that h(n) = 0 is admissible because it never overestimates the cost to reach the goal, and this makes statement D true. The instructor also notes that best-first search is not optimal (making A false), and recursive best-first search has poor space complexity, so C is true. The correct answer is determined to be A and D only, as both are false statements.

This segment teaches the evaluation of search algorithm properties—optimality, completeness, and admissibility—through a multiple-choice question. The instructor analyzes each statement: A is false because best-first search lacks optimality; B is true as A* satisfies completeness and optimality with admissible heuristics; C is false due to incorrect complexity claims about recursive best-first search; D is true because h(n) = 0 never overestimates cost, making it admissible. Handwritten annotations reinforce key concepts like 'h(n)=0 → admissible'. The lesson resolves doubts about algorithm correctness, particularly around heuristic validity and the conditions under which search methods guarantee optimal solutions.

Loading lesson…