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UNIT-IV
PLANNING
Syllabus
Introduction to
Planning
• Planning is nothing but deciding a
set of actions to be performed in
agent environment based on the
perception to achieve the decided
goal.
• To reach a particular destination
first we should find the best route
and then identify a set of actions to
be done at a particular time is
called planning.
Tasks in Planning
Domain
description
Action
specification
Goal
description
Types of Planning
 Classical Planning
 Fully observable
 Deterministic
 Finite
 Static
 Discrete
• Non-Classical Planning
• Partially observable
• Stochastic
Languages used for Planning
STRIPS (Stanford Research Institute Problem Solver)
ADL (Action Description Language)
The expressiveness and extensions of STRIPS are lower
than ADL
Planning with STATE SPACE SEARCH
Forward state space search algorithm
Backward state space search algorithm
Heuristic for state space search
Forward state space search
◦ It is also called as progression planning.
◦ Planning with forward state-space search is similar to
the problem-solving approach.
◦ Forward search is an algorithm that searches forward
from the initial state of the world to try to find a state
that satisfies the goal formula.
Steps
involved in
Forward
Search
Algorithm
Initial State
Actions
Goal Test
Step Cost
Example: Air Cargo Problem
There are two planes called P1 & P2
located at Airport A and are moved to
Airport B
Forward Search Algorithm
Drawbacks of FSSS
FSSS does not address the irrelevant action
problems and this approach quickly bogs
down without a good heuristic.
Backward state space search
 It is also called as regression planning.
 Want to generate possible predecessors of a given goal state, work
backwards toward the initial state.
 Backward Planning is also known as backward reasoning or goal directed
reasoning. It is preferred when the branching factor in reverse direction is
less than in forward direction.
 Backward planning is sometimes better as we start with the goal and thus
the visibility of the goal helps us choosing the moves
Backward state space search
Planning Graph
The Planning graph is based on the idea of reachability analysis,
which is a process of computing whether a set of states is
reachable or not from an initial set of states.
Graphplan is an algorithm for automated planning developed by
Avrim Blum and Merrick Furst in 1995.
Planning Graph
Planning graphs are an efficient way to create a representation of
a planning problem that can be used to
Achieve better heuristic estimates
Directly construct plans
Planning graphs only work for propositional problems.
Steps in the Planning Graphs
Example:
Have Cake
and Eat
Cake too
Steps
involved
in POP
EXAMPLE:
Unit-IV.pptx
Unit-IV.pptx
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Unit-IV.pptx

  • 3. Introduction to Planning • Planning is nothing but deciding a set of actions to be performed in agent environment based on the perception to achieve the decided goal. • To reach a particular destination first we should find the best route and then identify a set of actions to be done at a particular time is called planning.
  • 5. Types of Planning  Classical Planning  Fully observable  Deterministic  Finite  Static  Discrete • Non-Classical Planning • Partially observable • Stochastic
  • 6. Languages used for Planning STRIPS (Stanford Research Institute Problem Solver) ADL (Action Description Language) The expressiveness and extensions of STRIPS are lower than ADL
  • 7.
  • 8. Planning with STATE SPACE SEARCH Forward state space search algorithm Backward state space search algorithm Heuristic for state space search
  • 9. Forward state space search ◦ It is also called as progression planning. ◦ Planning with forward state-space search is similar to the problem-solving approach. ◦ Forward search is an algorithm that searches forward from the initial state of the world to try to find a state that satisfies the goal formula.
  • 11. Example: Air Cargo Problem There are two planes called P1 & P2 located at Airport A and are moved to Airport B
  • 13. Drawbacks of FSSS FSSS does not address the irrelevant action problems and this approach quickly bogs down without a good heuristic.
  • 14. Backward state space search  It is also called as regression planning.  Want to generate possible predecessors of a given goal state, work backwards toward the initial state.  Backward Planning is also known as backward reasoning or goal directed reasoning. It is preferred when the branching factor in reverse direction is less than in forward direction.  Backward planning is sometimes better as we start with the goal and thus the visibility of the goal helps us choosing the moves
  • 16.
  • 17. Planning Graph The Planning graph is based on the idea of reachability analysis, which is a process of computing whether a set of states is reachable or not from an initial set of states. Graphplan is an algorithm for automated planning developed by Avrim Blum and Merrick Furst in 1995.
  • 18. Planning Graph Planning graphs are an efficient way to create a representation of a planning problem that can be used to Achieve better heuristic estimates Directly construct plans Planning graphs only work for propositional problems.
  • 19. Steps in the Planning Graphs
  • 20.
  • 22.
  • 23.
  • 24.
  • 25.