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Fixed inaccurate comments.
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csp.py

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@@ -7,7 +7,7 @@
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class CSP(search.Problem):
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"""This class describes finite-domain Constraint Satisfaction Problems.
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A CSP is specified by the following three inputs:
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A CSP is specified by the following inputs:
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vars A list of variables; each is atomic (e.g. int or string).
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domains A dict of {var:[possible_value, ...]} entries.
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neighbors A dict of {var:[var,...]} that for each variable lists
@@ -33,7 +33,7 @@ class CSP(search.Problem):
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curr_domains[var] Slot: remaining consistent values for var
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Used by constraint propagation routines.
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The following methods are used only by graph_search and tree_search:
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succ() Return a list of (action, state) pairs
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succ(a) Return a list of (action, state) pairs
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goal_test(a) Return true if all constraints satisfied
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The following are just for debugging purposes:
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nassigns Slot: tracks the number of assignments made

games.py

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@@ -281,6 +281,5 @@ def __init__(self, h=7, v=6, k=4):
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TicTacToe.__init__(self, h, v, k)
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def legal_moves(self, state):
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"Legal moves are any square not yet taken."
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return [(x, y) for (x, y) in state.moves
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if y == 0 or (x, y-1) in state.board]

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