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Published byAlban Ferguson Modified over 9 years ago
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Review Test1
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Robotics & Future Technology
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Future of Intelligent Systems / Ray Kurzweil futurist Ray Kurzweil / A Long Bet A Long Bet / Robot Soccer Robot Soccer / BBC News - What happened to the Robotic Age?What happened to the Robotic Age / Robotic Dance? Robotic Dance? / Ray Kurzweil futurist Ray Kurzweil / A Long Bet A Long Bet / Robot Soccer Robot Soccer / BBC News - What happened to the Robotic Age?What happened to the Robotic Age / Robotic Dance? Robotic Dance?
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REVIEW of some important concepts to remember… REVIEW of some important concepts to remember… CHAPTER 5
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Incremental Problem Formulation (The N-Queens Problem)
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Constraint Satisfaction A constraint satisfaction problem (CSP) is a problem composed of variables and constraints. The objective is to assign values to variable in such a way that all of the constraints are satisfied. A CSP can be more formally viewed as a triple where: / D represents a set of n domains / X represents a set of n variables, each variable x i takes it value from D i / C represents a set of constraints. A constraint satisfaction problem (CSP) is a problem composed of variables and constraints. The objective is to assign values to variable in such a way that all of the constraints are satisfied. A CSP can be more formally viewed as a triple where: / D represents a set of n domains / X represents a set of n variables, each variable x i takes it value from D i / C represents a set of constraints.
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Two types of CSPs / Finite domain CSPs / Queens, Domains, Boolean / Infinite Domain CSPs / If Job1 takes 5 days, then Job3 will start / Job1 +5 < Job3 / Finite domain CSPs / Queens, Domains, Boolean / Infinite Domain CSPs / If Job1 takes 5 days, then Job3 will start / Job1 +5 < Job3
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thrashing Wasteful ” backtracking is known as
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Variable & Value Ordering / Variable order selection seldom results in the most efficient search / One efficient strategy / Minimum Remaining Value (MRV) which chooses the value with the fewest legal values / A.K.A “Most Constrained Value” / A.K.A “Fail-First” Heuristic because it is the most likely to cause failure first / Variable order selection seldom results in the most efficient search / One efficient strategy / Minimum Remaining Value (MRV) which chooses the value with the fewest legal values / A.K.A “Most Constrained Value” / A.K.A “Fail-First” Heuristic because it is the most likely to cause failure first
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Propagating through constraints / When every variable X is assigned, the forward checking process looks at each unassigned variable Y AND Deletes from Y’s domain any value that is inconsistent with the value chosen for X. / Forward Checking is a better use of constraints / Think of Forward Checking as a way to incrementally compute the info needed for MRV to do its job
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Arc Consistency nother backtrack-based algorithm that is even more efficient is called the maintaining arc consistency (MAC) algorithm. / Arc Consistency provides fast method of constraint propagation stronger than forward checking. / Arc Consistency can be provided as preprocessing step (just as forward checking can be used to preprocess). nother backtrack-based algorithm that is even more efficient is called the maintaining arc consistency (MAC) algorithm. / Arc Consistency provides fast method of constraint propagation stronger than forward checking. / Arc Consistency can be provided as preprocessing step (just as forward checking can be used to preprocess).
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MAC Algorithm p146 / Rather than just revising each domain corresponding with the value of each instantiated variable MAC makes the network arc-consistent with respect to the instantiated variables (all arcs must be consistent). / MAC is applied repeatedly until no more inconsistencies remain. / Node Consistency / 1-consistency means that each individual variable by itself is consistent (node consistency) / 2-consistency is arc consistency / 3-consistency means that any pair of adjacent variables can always be extended to a third neighboring variable (i.e. path consistency or AC-3) / AC-3 uses a queue to keep track of nodes that need to be checked for inconsistency / Rather than just revising each domain corresponding with the value of each instantiated variable MAC makes the network arc-consistent with respect to the instantiated variables (all arcs must be consistent). / MAC is applied repeatedly until no more inconsistencies remain. / Node Consistency / 1-consistency means that each individual variable by itself is consistent (node consistency) / 2-consistency is arc consistency / 3-consistency means that any pair of adjacent variables can always be extended to a third neighboring variable (i.e. path consistency or AC-3) / AC-3 uses a queue to keep track of nodes that need to be checked for inconsistency
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Intelligent backtracking: looking backward / Chronological backtracking: a policy for when a branch of the search fails by backing up to the preceding variable and try a different value for it / Chronological uses the more recent decision point to revisit / Chronological backtracking: a policy for when a branch of the search fails by backing up to the preceding variable and try a different value for it / Chronological uses the more recent decision point to revisit
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Things that cause a failure / The conflict set / Backjumping backtracks to the most recent variable in the conflict set / The conflict set / Backjumping backtracks to the most recent variable in the conflict set
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