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CIS730-Lecture-20-20061011

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Computing & Information Sciences. Kansas State University ... Concepts: utility, reinforcements, game trees. Static evaluation under resource limitations ... – PowerPoint PPT presentation

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Title: CIS730-Lecture-20-20061011


1
Lecture 21 of 42
Classical Planning Discussion Search Review
Friday, 13 October 2006 William H.
Hsu Department of Computing and Information
Sciences, KSU KSOL course page
http//snipurl.com/v9v3 Course web site
http//www.kddresearch.org/Courses/Fall-2006/CIS73
0 Instructor home page http//www.cis.ksu.edu/bh
su Reading for Next Class Chapters 1 10
except 4.4 4.5, Russell Norvig 2nd edition
2
Lecture Outline
  • Todays Reading Review Chapters 1-10, RN 2e
  • Next Wednesdays Reading Section 11.3, RN 2e
  • Wednesday
  • Classical planning
  • STRIPS representation
  • Basic algorithms
  • Today
  • Midterm exam review search and constraints, game
    tree search
  • Planning continued
  • Midterm Exam 16 Oct 2006
  • Remote students have exam agreement faxed to DCE
  • Exam will be faxed to proctors Wednesday or Friday

3
Midterm Review IAs, SearchUnclear Points?
  • Artificial Intelligence (AI)
  • Operational definition study / development of
    systems capable of thought processes
    (reasoning, learning, problem solving)
  • Constructive definition expressed in artifacts
    (design and implementation)
  • Intelligent Agent Framework
  • Reactivity vs. state
  • From goals to preferences (utilities)
  • Methodologies and Applications
  • Search game-playing systems, problem solvers
  • Planning, design, scheduling systems
  • Control and optimization systems
  • Machine learning hypothesis space search (for
    pattern recognition, data mining)
  • Search
  • Problem formulation state space (initial /
    operator / goal test / cost), graph
  • State space search approaches
  • Blind (uninformed) DFS, BFS, BB
  • Heuristic (informed) Greedy, Beam, A/A
    Hill-Climbing, SA

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Midterm Review KR, Logic, Proof TheoryUnclear
Points?
  • Logical Frameworks
  • Knowledge Bases (KB)
  • Logic in general representation languages,
    syntax, semantics
  • Propositional logic
  • First-order logic (FOL, FOPC)
  • Model theory, domain theory possible worlds
    semantics, entailment
  • Normal Forms
  • Conjunctive Normal Form (CNF)
  • Disjunctive Normal Form (DNF)
  • Horn Form
  • Proof Theory and Inference Systems
  • Sequent calculi rules of proof theory
  • Derivability or provability
  • Properties
  • Knowledge bases, WFFs consistency,
    satisfiability, validity, entailment
  • Proof procedures soundness, completeness
    decidability (decision)

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13
Midterm Review Game TreesUnclear Points?
  • Games as Search Problems
  • Frameworks
  • Concepts utility, reinforcements, game trees
  • Static evaluation under resource limitations
  • Family of Algorithms for Game Trees Minimax
  • Static evaluation algorithm
  • To arbitrary ply
  • To fixed ply
  • Sophistications iterative deepening, alpha-beta
    pruning
  • Credit propagation
  • Intuitive concept
  • Basis for simple (delta-rule) learning algorithms
  • State of The Field
  • Uncertainty in Games Expectiminimax and Other
    Algorithms

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15
Search versus Planning 1
Adapted from slides by S. Russell, UC Berkeley
16
Planning in Situation Calculus
Adapted from slides by S. Russell, UC Berkeley
17
STRIPS Operators
Adapted from slides by S. Russell, UC Berkeley
18
State Space versus Plan Space
Adapted from slides by S. Russell, UC Berkeley
19
Describing Actions 1Frame, Qualification, and
Ramification Problems
Adapted from slides by S. Russell, UC Berkeley
20
Describing Actions 2Successor State Axioms
Adapted from slides by S. Russell, UC Berkeley
21
Making Plans
Adapted from slides by S. Russell, UC Berkeley
22
Making PlansA Better Way
Adapted from slides by S. Russell, UC Berkeley
23
First-Order LogicSummary
Adapted from slides by S. Russell, UC Berkeley
24
Partially-Ordered Plans
Adapted from slides by S. Russell, UC Berkeley
25
POP Algorithm 1Sketch
Adapted from slides by S. Russell, UC Berkeley
26
POP Algorithm 2Subroutines and Properties
Adapted from slides by S. Russell, UC Berkeley
27
Clobbering andPromotion / Demotion
Adapted from slides by S. Russell, UC Berkeley
28
Summary Points
  • Previously Logical Representations and Theorem
    Proving
  • Propositional, predicate, and first-order logical
    languages
  • Proof procedures forward and backward chaining,
    resolution refutation
  • Today Introduction to Classical Planning
  • Search vs. planning
  • STRIPS axioms
  • Operator representation
  • Components preconditions, postconditions (ADD,
    DELETE lists)
  • Thursday More Classical Planning
  • Partial-order planning (NOAH, etc.)
  • Limitations

29
Terminology
  • Classical Planning
  • Planning versus search
  • Problematic approaches to planning
  • Forward chaining
  • Situation calculus
  • Representation
  • Initial state
  • Goal state / test
  • Operators
  • Efficient Representations
  • STRIPS axioms
  • Components preconditions, postconditions (ADD,
    DELETE lists)
  • Clobbering / threatening
  • Reactive plans and policies
  • Markov decision processes

Adapted from slides by S. Russell, UC Berkeley
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