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Booking a flight |
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Scheduling a meeting |
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Playing chess |
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VLSI Layout |
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Construction Planning |
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Parsing Grammars |
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Robot Navigation |
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Assembly Sequencing |
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etc. etc. etc. |
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Simple Search Problem-Solving Agent |
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4 Parts of a Search Problem |
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Example Search Problems |
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General Search |
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Breadth-First Search |
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Depth-First Search |
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Etc. |
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Single-state problem - current state known, each
action maps to a single state |
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Multiple-state problem - current state or
effects of actions unknown |
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Contingency problem - uncertainty reduced by
sensing during execution of actions |
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Exploration problem - no information about the
effects of actions |
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Uninformed - no information given to aid search |
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State space: |
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Initial state |
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Operators (or successor function) |
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Goal test |
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Path cost |
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8-puzzle |
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8-queens problem Þ problem formulation is important! |
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Booking a flight |
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Scheduling a meeting |
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Playing chess |
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VLSI Layout |
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Construction Planning |
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Parsing Grammars |
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Robot Navigation |
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Assembly Sequencing |
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etc. etc. etc. |
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General approach |
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Criteria for comparing tradeoffs |
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Search strategies: |
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Breadth-first search |
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Uniform cost search |
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Depth-first search |
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Depth-limited search |
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Iterative deepening search |
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Bidirectional search |
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Island-driven search |
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Completeness - guaranteed to find solution if
there is one? |
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Time complexity - how much time does it take to
find a solution? |
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Space complexity - how much memory does it take
to find a solution? |
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Optimality - does it find the best of all
possible solutions? |
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Time complexity: |
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Branching factor b |
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Search depth d |
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O(b^d) |
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Space complexity also O(b^d) |
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Same time/space complexity. Which is the more
critical limit? |
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Time complexity O(b^d) |
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Space complexity O(b*d) |
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What’s the tradeoff? |
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Neither optimal nor complete |
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Some ways of dealing with repeated states: |
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Don’t avoid repeated states |
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Don’t immediately repeat the same state |
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Don’t introduce cycles in paths |
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Don’t repeat states |
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Problem formulation |
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Depth-first search with a depth limit. |
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No nodes beyond the depth limit are enqueued. |
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Sequential runs of depth-limited search with
increasing depth: |
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Depth-limited search (limit = 1) |
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Depth-limited search (limit = 2) |
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Depth-limited search (limit = 3) |
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Etc. |
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Search both directions until search frontiers
meet. |
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How to drive from Palo Alto, CA to Gettysburg,
PA? |
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Different levels of granularity help reduce
problem complexity |
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“Time is money.” |
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Search takes time. |
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Point of diminishing returns with real-time
search problems |
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Each search space state as a set of world
states. |
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Goal test a conjunction of goal tests |
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Problems with this approach |
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Minimizing uncertainty |
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Notes