Plan Space Planning

Duration: 5 min

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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
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  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
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  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 lecture introduces Plan Space Planning, also known as Non-Linear Planning, contrasting it with traditional state-based planning. The instructor explains that this approach works with plan structures, allowing the modification or extension of any part of the plan to reach a final solution. Key characteristics include the ability to shift attention midway and solve complex problems like the Sussman anomaly. The lecture transitions to Partial Order Plans, defining them as sets of actions with a partial ordering. An example of getting ready in the morning, specifically putting on shoes, is used to illustrate how independent actions can be ordered flexibly without affecting the final goal.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The instructor introduces Plan Space Planning (Non-Linear Planning) using a slide that highlights its ability to modify or extend any part of a plan. She writes 'Search space of plans' on the board, contrasting this with state-based planning where the planner looks at a state and a goal. The slide text emphasizes that you can 'modify any part of the plan' and 'shift their attention midway,' which allows solving problems like the Sussman anomaly. The instructor notes that unlike linear planning, this approach is not constrained to focus on one sub-goal continuously.

  2. 2:00 – 4:59 02:00-04:59

    The lecture moves to Partial Order Plans, defining them as a set of actions with a partial ordering representing a 'before' relation. The instructor writes 'plan -> refine & define totally' and 'plan flexibility' on the slide. She provides an example of 'Getting ready in the morning to go out,' showing a diagram where 'LeftShoeOn' and 'RightShoeOn' are parallel actions between Start and Finish. She explains that whether the left or right shoe is put on first does not matter, illustrating the concept of partial ordering where total ordering is not strictly required for independent actions.

The video progresses from a high-level definition of Plan Space Planning to specific implementations like Partial Order Plans. Initially, the instructor establishes that Plan Space Planning searches the space of plans rather than states, offering flexibility to modify plans and solve anomalies like the Sussman anomaly. This sets the stage for Partial Order Plans, where actions are defined by a partial ordering. The shoe-putting example concretely demonstrates this concept: while actions must happen between start and finish, the specific order of independent actions (left vs. right shoe) is irrelevant, showcasing the efficiency and flexibility of non-linear planning strategies.

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