What Are Constraint Satisfaction Problems?(slides5) Flashcards
CSP state
defined by variables Xi with values from domain Di
CSP goal test
a set of constraints specifying allowable combinations of values for subsets of variables
Constraint Satisfaction Problems
give a standard factorization of the state
general purpose heuristics
the main idea is to reduce the search space by identifying constraint violations
CSP sets and domains
set or variables X= {X1, X2, …., Xn}
set of domains D={D1,D2,…,Dn}
-variable Xi takes value from domain Di
-Domain can also be same for all variables
CSP constraint sets
C={ci=(scopei,reli) | i=1,…,h}
- scopei: subset of X, the variables that are constrained by ci
- reli: is a relations and tells us which simultaneous assignments to variables in scopei are allowed or not allowed
CSP Varieties of constraints
Unary
Binary
Higher-order
CSP Unary constraints
constraints that involve a single variable
-eg, SA != green
CSP Binary Constraints
constraints that involve pairs of variables
-eg, SA != WA
CSP Higher Order constraints
involve 3 or more variables
-e.g., cryptarithmetic column constraints
Binary CSP
each constraint relates two variables
constraint graph
nodes are variables, arcs are constraints (only works with Binary CSP)
CSP binary conversion
Any CSP can be converted into one with only binary constraints
2 known techniques:
-dual graph method
-hidden variable method
translations are polynomial if constraints are represented extensionally
Varieties of CSP variables
Discrete Variables
continuous variables
CSP Discrete Variables
finite domains
infinite domains
CSP finite domains
- n variabls, domain size d –> O(d^n) complete assignments
- e.g., Boolean CSPs, incl. ~Boolean satisfiability (NP-complete)