Practice question on Search Algorithm 1

Duration: 1 min

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Module outline

  1. About Course: UPPSC Course Overview
  2. Interview Preparation & Guidance: Interview Preparation
  3. Paper 1 | General Hindi: भाषा, लिपि, ध्वनि, वर्ण, अक्षर, स्वर, व्यंजन, मात्रा और संयुक्ताक्षर, वर्तनी, वर्ण-विन्यास, अनुस्वार, अनुनासिक, चंद्रबिंदु और ‘र’ के रूप, शब्द, पद और शब्द-भेद, संज्ञा और सर्वनाम, विशेषण और क्रिया, लिंग, वचन, पुरुष और कारक, काल, वाच्य, वाक्य और वाक्य-भेद, वर्णमाला, समास, संधि, विलोम शब्द, पर्यायवाची शब्द, सामान्य अशुद्धियाँ, अनेक शब्दों के लिए एक शब्द, मुहावरे और लोकोक्तियाँ, अपठित गद्यांश और अपठित पद्यांश, Multi-Topic Content (Cross-Concept Material)
  4. Paper 2 | General Studies: State Wise GK, Polity, Geography, History, GK- Current Affairs
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  8. Paper 1 | Computer Organization and Architecture: Basics of COA, Programming the Basic Computer, Cache Memory Organization, Input Output Organisation, Instr Formats & Modes, Register Transfer and Microoperations, Control Unit Design
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  10. Paper 1 | Design and Analysis of Algorithms: Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos, Advanced Algorithms
  11. Paper 1 | Data Structures: Introduction to DS, Array, Linked List, Stack, Queue, Tree, Graphs, Hashing
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  13. Paper 1 | Software Project Management: Software Project Management
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  16. Paper 2 | Artificial Intelligence & High Performance Computing: Approaches to AI, Search Algorithms, Game Playing, Knowledge Representation, Planning, Multi Agent Systems, Natural Language Processing, Emerging Tech Trends
  17. Paper 2 | Image Processing: Digital Image Fundamentals, Image Enhancement, Image Restoration, Color Image Processing, Image Compression
  18. 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
  19. Paper 2 | Computer Graphics: Basics of Computer Graphics, 2-D Geometrical Transforms and Viewing, 3-D Object Representation, Geometric Transformations and Viewing
  20. Paper 2 | Web Technologies: Website, Browser & Services, Internet Fundamentals, Web Design & Development, Protocols & Services, Web Publishing & Hosting, Server Side & Security, Emerging Technologies, HTML Basics, JavaScript-Basics, Java
  21. Paper 2 | Soft Computing: Fuzzy Sets, Artificial Neural Networks, Genetic Algorithms
  22. Paper 2 | Distributed System: Distributed Systems
  23. UPPSC Live Class Recordings: UPPSC Polytechnic Lecturer 2025 (CS)
  24. Previous Year Papers:
  25. Mock Test:
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

The video presents a multiple-choice question from a UGC NET exam (Dec 2023) regarding the time complexity of various search algorithms. The question asks to match algorithms in List I (Hill climbing, Best first search, A* Search, Depth first search) with their corresponding time complexities in List II (O(b^d), O(bd), O(1), O(b^m)). The instructor highlights the options and reveals the correct answer as option (i), which maps Hill climbing to O(1), Best first search to O(b^d), A* Search to O(b^m), and Depth first search to O(bd). The video concludes by introducing a new question about the shortcomings of the hill climbing algorithm, specifically mentioning local maxima, plateaus, and ridges. The screen displays a PDF file named "CSO practice file.pdf" with a watermark "KNOWLEDGE GATE".

Chapters

  1. 0:00 – 1:02 00:00-01:02

    The video remains static on the PDF page for the duration. The cursor moves to highlight List I items (A) through (D), then List II items (I) through (IV). It then moves to the options below, highlighting option (i) as the correct match. Finally, the cursor scrolls down to show the next question about hill climbing shortcomings. The instructor's face is visible in the top right corner.

The lecture segment focuses on evaluating the computational complexity of heuristic search strategies. By matching specific algorithms like Hill Climbing and A* Search with their Big O notations, the instructor reinforces the theoretical understanding of how these algorithms scale with branching factor (b) and depth (d or m). The correct matching highlights that Hill Climbing is often constant time O(1) in simple local search contexts, while Depth First Search is linear O(bd) or O(b^m) depending on the specific formulation, though the answer key suggests O(bd) for DFS here. The transition to the next question about local maxima and plateaus suggests a shift from complexity analysis to the limitations and failure modes of these search techniques.

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