Unformatted text preview:

Review for the Midterm ExamThe Chapters We’ve CoveredChapter 1: Introduction and Overview2: Representations for Classical PlanningChapter 3: Complexity of Classical PlanningChapter 4: State-Space PlanningChapter 5: Plan-Space PlanningChapter 6: Planning-Graph Techniques7: Propositional Satisfiability TechniquesChapter 16: Planning Based on MDPs17: Planning based on Model CheckingThe ExamStudying for the ExamMiscellaneousDana Nau: Lecture slides for Automated PlanningLicensed under the Creative Commons Attribution-NonCommercial-ShareAlike License: http://creativecommons.org/licenses/by-nc-sa/2.0/1Review for the Midterm ExamLecture slides forAutomated Planning: Theory and PracticeDana S. NauUniversity of Maryland09:59 AM January 14, 2019Dana Nau: Lecture slides for Automated PlanningLicensed under the Creative Commons Attribution-NonCommercial-ShareAlike License: http://creativecommons.org/licenses/by-nc-sa/2.0/2The Chapters We’ve CoveredChapter 1: IntroductionChapter 2: Representations for Classical PlanningChapter 3: Complexity of Classical PlanningChapter 4: State-Space PlanningChapter 5: Plan-Space PlanningChapter 6: Planning-Graph TechniquesChapter 7: Propositional Satisfiability TechniquesChapter 16: Planning based on MDPsChapter 17: Planning based on Model CheckingDana Nau: Lecture slides for Automated PlanningLicensed under the Creative Commons Attribution-NonCommercial-ShareAlike License: http://creativecommons.org/licenses/by-nc-sa/2.0/3Chapter 1: Introduction and Overview1.1: First Intuitions on Planning 1.2: Forms of planning 1.3: Domain-Independent Planning 1.4: Conceptual Model for Planning 1.5: Restricted Model 1.6: Extended Models 1.7: A Running Example: Dock-Worker Robots No questions on Chapter 1Dana Nau: Lecture slides for Automated PlanningLicensed under the Creative Commons Attribution-NonCommercial-ShareAlike License: http://creativecommons.org/licenses/by-nc-sa/2.0/42: Representations for Classical Planning2.1: Introduction 2.2: Set-Theoretic Representation 2.2.1: Planning Domains,Problems, and Solutions 2.2.2: State Reachability 2.2.3: Stating a Planning Problem 2.2.4: Properties of theSet-theoretic Representation 2.3: Classical Representation 2.3.1: States 2.3.2: Operators and Actions 2.3.3: Plans, Problems, & Solutions2.3.4: Semantics of Classical Reps2.4: Extending the Classical Rep.2.4.1: Simple Syntactical Extensions 2.4.2: Conditional Planning Operators 2.4.3: Quantified Expressions 2.4.4: Disjunctive Preconditions 2.4.5: Axiomatic Inference 2.4.6: Function Symbols 2.4.7: Attached Procedures 2.4.8: Extended Goals 2.5: State-Variable Representation 2.5.1: State Variables 2.5.2: Operators and Actions 2.5.3: Domains and Problems 2.5.4: Properties 2.6: Comparisons No questions on these topics:Dana Nau: Lecture slides for Automated PlanningLicensed under the Creative Commons Attribution-NonCommercial-ShareAlike License: http://creativecommons.org/licenses/by-nc-sa/2.0/5Chapter 3: Complexity of Classical Planning3.1: Introduction 3.2: Preliminaries 3.3: Decidability and Undecidability Results 3.4: Complexity Results 3.4.1: Binary Counters 3.4.2: Unrestricted Classical Planning 3.4.3: Other results 3.5: Limitations You don’t need to know the details of the complexity tables, but you should know the basic concepts, e.g.:- What does it mean to allow or disallow function symbols, negative effects, etc.?- What’s the difference between giving the operators in the input or in advance?Dana Nau: Lecture slides for Automated PlanningLicensed under the Creative Commons Attribution-NonCommercial-ShareAlike License: http://creativecommons.org/licenses/by-nc-sa/2.0/6Chapter 4: State-Space PlanningNo questions on this topicDana Nau: Lecture slides for Automated PlanningLicensed under the Creative Commons Attribution-NonCommercial-ShareAlike License: http://creativecommons.org/licenses/by-nc-sa/2.0/75.1: Introduction 5.2: The Search Space of Partial Plans 5.3: Solution Plans 5.4: Algorithms for Plan Space Planning 5.4.1: The PSP Procedure5.4.2: The PoP Procedure 5.5: Extensions 5.6: Plan Space Versus State Space Planning Chapter 5: Plan-Space PlanningNo questions on these topicsDana Nau: Lecture slides for Automated PlanningLicensed under the Creative Commons Attribution-NonCommercial-ShareAlike License: http://creativecommons.org/licenses/by-nc-sa/2.0/8Chapter 6: Planning-Graph Techniques6.1: Introduction 6.2: Planning Graphs 6.2.1: Reachability Trees 6.2.2: Reachability with Planning Graphs 6.2.3: Independent Actions and Layered Plans 6.2.4: Mutual Exclusion Relations 6.3: The Graphplan Planner 6.3.1: Expanding the Planning Graph 6.3.2: Searching the Planning Graph 6.3.3: Analysis of Graphplan 6.4: Extensions and Improvements of Graphplan 6.4.1: Extending the Language 6.4.2: Improving the Planner 6.4.3: Extending the Independence Relation use my lecture notesNo questions on these topicsDana Nau: Lecture slides for Automated PlanningLicensed under the Creative Commons Attribution-NonCommercial-ShareAlike License: http://creativecommons.org/licenses/by-nc-sa/2.0/97: Propositional Satisfiability Techniques7.1: Introduction 7.2: Planning problems as Satisfiability problems 7.2.1: States as propositional formulas 7.2.2: State transitions as propositional formulas 7.2.3: Planning problems as propositional formulas 7.3: Planning by Satisfiability 7.3.1: Davis-Putnam 7.3.2: Stochastic Procedures7.4: Different Encodings 7.4.1: Action Representation 7.4.2: Frame axioms No questions on these topicsNo questions on these topicsDana Nau: Lecture slides for Automated PlanningLicensed under the Creative Commons Attribution-NonCommercial-ShareAlike License: http://creativecommons.org/licenses/by-nc-sa/2.0/10Chapter 16: Planning Based on MDPs16.1: Introduction 16.2: Planning in Fully Observable Domains 16.2.1: Domains, Plans, and Planning Problems 16.2.2: Planning Algorithms 16.3: Planning under Partial Observability 16.3.1: Domains, Plans, and Planning Problems 16.3.2: Planning Algorithms 16.4: Reachability and Extended Goals No questionson these topicsDana Nau: Lecture slides for Automated PlanningLicensed under the Creative Commons Attribution-NonCommercial-ShareAlike License:


View Full Document
Download Review for the Midterm Exam
Our administrator received your request to download this document. We will send you the file to your email shortly.
Loading Unlocking...
Login

Join to view Review for the Midterm Exam and access 3M+ class-specific study document.

or
We will never post anything without your permission.
Don't have an account?
Sign Up

Join to view Review for the Midterm Exam 2 2 and access 3M+ class-specific study document.

or

By creating an account you agree to our Privacy Policy and Terms Of Use

Already a member?