Solvable Vs Unsolvable Problem Part-1

Duration: 10 min

This video lesson is available to enrolled students.

Return to /learn/BIHAR-STET-COMPUTER-SCIENCE-COMPLETE-COURSE/unit-11-theory-of-computation/regular-language-properties/decidability-basics/asset-solvable-vs-unsolvable-problem-part-1 after enrolling

Inside: a video lesson and guided study material.

Module outline

  1. About the course: About the Course
  2. Mathematical Aptitude: संख्या पद्धति / Number System, महत्तम समापवर्तक और लघुत्तम समापवर्त्य / HCF and LCM, Divisibility Rules, प्रतिशत / Percentage, अनुपात और समानुपात / Ratio and Proportion, औसत / Average, लाभ, हानि और बट्टा / Profit, Loss and Discount, समय और कार्य / Time and Work, घन क्षेत्रमिति / Solid Mensuration, साधारण और चक्रवृद्धि ब्याज / Simple and Compound Interest, समय, चाल और दूरी / Time, Speed and Distance, Age Problems, मिश्रण और एलिगेशन / Mixture and Alligation, Algebra, सरलीकरण, घातांक और करणी / Simplification, Indices and Surds, Pipe and Cistern, Trigonometry, Statistics, आँकड़ा निर्वचन / Data Interpretation, Arithmetic, समुच्चय, संबंध, फलन और विविक्त गणित / Sets, Relations, Functions and Discrete Mathematics, संख्या पद्धति और संख्या सिद्धांत / Number Systems and Number Theory, निर्देशांक ज्यामिति, सदिश और त्रिविमीय ज्यामिति / Coordinate Geometry, Vectors and 3D Geometry, बहुपद, समीकरण और सम्मिश्र संख्याएँ / Polynomials, Equations and Complex Numbers
  3. Logical Reasoning: श्रेणी / Series, कूट लेखन एवं कूट वाचन / Coding-Decoding, सादृश्यता एवं वर्गीकरण / Analogy and Classification, रक्त संबंध / Blood Relations, दिशा एवं दूरी / Direction and Distance, क्रम एवं रैंकिंग / Order and Ranking, अशाब्दिक तर्क / Non-Verbal Reasoning, बैठक व्यवस्था एवं पहेलियाँ / Seating Arrangement and Puzzles, Syllogisms, वेन आरेख, न्याय वाक्य एवं असमानता / Venn Diagrams, Syllogism and Inequalities, गणितीय संक्रियाएँ एवं लुप्त संख्या / Mathematical Operations and Missing Numbers, वर्णमाला एवं संख्या परीक्षण / Alphabet and Number Test, कथन आधारित तार्किक विवेचन / Statement-Based Reasoning, Analytical Reasoning (Counting Figures Reasoning), घन, पासा एवं आकृतियों की गिनती / Cubes, Dice and Figure Counting, कैलेंडर एवं घड़ी / Calendar and Clock, Clock
  4. General Knowledge: वैज्ञानिक उपलब्धियाँ और अनुसंधान / Scientific Achievements and Research, Chemistry, Biology, History, Geography, Polity, Indian Economy, समसामयिकी / Current Affairs, Static General Knowledge, राज्य विशेष सामान्य ज्ञान / State-Specific General Knowledge
  5. Art of Teaching: शिक्षण-अधिगम प्रक्रिया एवं कक्षा प्रबंधन / Teaching-Learning Process and Classroom Management, Learners & Learning Process, Factors Affecting Teaching, शिक्षण विधियाँ एवं उपागम / Teaching Methods and Approaches, सूक्ष्म शिक्षण एवं कक्षा संप्रेषण / Microteaching and Classroom Communication, शिक्षण सहायक सामग्री एवं शैक्षिक तकनीकी / Teaching Aids and Educational Technology, आकलन एवं मूल्यांकन / Assessment and Evaluation, शिक्षक: गुण, व्यावसायिक नैतिकता एवं विकास / Teacher: Qualities, Professional Ethics and Development, शैक्षिक नीतियाँ, अधिनियम एवं प्रशासन / Educational Policies, Acts and Administration, पाठ्यचर्या, कला एवं सह-शैक्षिक क्षेत्र / Curriculum, Arts and Co-curricular Areas, निर्देशन एवं परामर्श / Guidance and Counselling, दिव्यांग बच्चों की शिक्षा / Education of Children with Disabilities, Micro-Teaching & Teaching Skills, पाठ योजना / Lesson Planning
  6. Environmental Science: Environment
  7. Unit 1 | Digital Electronics: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Combinational Circuit, Sequential Circuits, Number System, Number Representation
  8. Unit 2 | COA: Basics of COA, Floating Point Rep, Cache Memory Organization, Input Output Organisation, Instr Formats & Modes, Control Unit Design, Register Transfer and Microoperations, Programming the Basic Computer
  9. Unit 3 | C Programming: C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling
  10. Unit 3 | Data Structures: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  11. Unit 4 | Algorithms: Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos, Advanced Algorithms
  12. Unit 5 | Operating System: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Threads & Process Creation, Deadlock, Memory Management, Virtual Memory, Disc Scheduling, File Management
  13. Unit 6 | Database Management System: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, File Organization & Indexing, Relational Algebra, SQL, Transaction Management, Concurrency Control
  14. Unit 7 | Computer Networks: Introduction to CN, Data Communication, 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, Application Layer
  15. Unit 8 | Software Engineering: Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management
  16. Unit 9 | Object Oriented Programming: OOPS with C++
  17. Unit 10 | Web Development: HTML Basics, CSS, JavaScript-Basics, XML, Node.js, Git & Github, PHP
  18. Unit 11 | 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
  19. Unit 12 | IoT: Emerging Tech Trends, Cloud Computing, कंप्यूटर नेटवर्क / Computer Networks
  20. Unit 13 | Artificial Intelligence: Approaches to AI, Search Algorithms, Game Playing, Knowledge Representation, Natural Language Processing, Artificial Neural Networks, Genetic Algorithms
  21. Unit 14 | E-Commerce: Electronic Data Interchange and E-Commerce, Role of Internet and Web Services, Security in Mobile and Wireless Computing, Physical Security and Cryptography Basics, Cyber Safety and Security
  22. Unit 15 | Multimedia: Multimedia
  23. Unit 16 | Python: Introduction to Python, Tokens, Variables, Data Types, I/O, Operators & Expressions, Control Flow & Looping, Collections & Strings, Functions & Modules, File Handling & Data Analysis, DSA using Python
  24. Full Length Mock Tests — General Paper:
  25. Full Length Mock Tests — Computer Science (Paper II):
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

This educational video lecture provides a foundational overview of computational problem classification and introduces the historical Konigsberg Bridge Problem. The instructor begins by presenting a hierarchical flowchart that categorizes all problems into Solvable and Unsolvable types. He further breaks down Solvable problems into Decidable and Undecidable categories, and finally into P Type and NP Type complexity classes. The lecture then transitions to graph theory, using the Konigsberg Bridge Problem as a case study. The instructor illustrates the physical layout of the city with its river and bridges, labeling landmasses A, B, C, and D. He demonstrates how to abstract this physical map into a mathematical graph, explaining the concept of traversing edges (bridges) exactly once. This segment highlights the origins of graph theory and the distinction between solvable and unsolvable problems in a practical context.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The instructor introduces the broad classification of problems using a flowchart diagram. The top node is labeled 'PROBLEM', which branches into 'SOLVABLE' and 'UNSOLVABLE'. The instructor points to the 'PROBLEM' box and then the 'SOLVABLE' box, establishing the primary dichotomy. He explains that every problem in computer science falls into one of these two main categories. The visual aid clearly shows the hierarchy, setting the stage for a deeper dive into computability theory.

  2. 2:00 – 5:00 02:00-05:00

    The lecture delves deeper into the 'SOLVABLE' branch of the flowchart. The instructor draws red arrows connecting 'PROBLEM' to 'SOLVABLE' and 'UNSOLVABLE' to emphasize the relationship. He explains that 'SOLVABLE' problems are further divided into 'DECIDABLE' and 'UNDECIDABLE'. He notes that 'DECIDABLE' problems are those for which an algorithm exists that always halts with a correct yes or no answer. The flowchart also shows 'DECIDABLE' branching into 'P TYPE' and 'NP TYPE', indicating complexity classes. The instructor uses hand gestures to trace the path from the root problem down to these specific types.

  3. 5:00 – 10:00 05:00-10:00

    The topic shifts to the 'Konigsberg Bridge Problem'. The slide displays a diagram of the city with a river and seven bridges connecting four landmasses labeled A, B, C, and D. The instructor explains the challenge: to find a path that crosses every bridge exactly once. He then converts this physical map into a graph representation, drawing nodes for the landmasses and edges for the bridges. He draws the graph on the right side of the screen, showing nodes A, B, C, D connected by lines. He discusses how this problem was historically significant and led to the birth of graph theory, illustrating the concept of Eulerian paths and circuits.

  4. 10:00 – 10:02 10:00-10:02

    The video concludes with the graph of the Konigsberg Bridge Problem fully displayed on the screen. The instructor is likely summarizing the key takeaway that this problem, while seemingly simple, was unsolvable in its original form, reinforcing the earlier discussion on unsolvable problems. The visual focus remains on the graph with nodes A, B, C, D and the connecting edges, serving as a final visual anchor for the lesson on graph theory and problem solvability.

The lecture effectively connects abstract computational theory with concrete historical examples. It starts by defining the landscape of problems (Solvable vs. Unsolvable) and their sub-categories (Decidable, P, NP). It then grounds these concepts in the Konigsberg Bridge Problem, showing how a real-world scenario can be modeled as a graph. This progression helps students understand not just the definitions of solvability, but also the historical context and practical application of graph theory in determining whether a problem can be solved.

Loading lesson…