Lab 2 2014
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We've learned a lot about different types of search in lecture the last several weeks. This problem set will involve implementing several search techniques. For each type of search you are asked to write, you will get a graph (with a list of nodes and a list of edges and a heuristic), a start node, and a goal node. | We've learned a lot about different types of search in lecture the last several weeks. This problem set will involve implementing several search techniques. For each type of search you are asked to write, you will get a graph (with a list of nodes and a list of edges and a heuristic), a start node, and a goal node. | ||
| - | A graph is a class, defined in <tt>search.py</tt> that has lists <tt>.nodes</tt> and <tt>.edges</tt> and a dictionary <tt>.heuristic</tt>. Nodes are just string names, but edges are dictionaries that contain each | + | A graph is a class, defined in <tt>search.py</tt> that has lists <tt>.nodes</tt> and <tt>.edges</tt> and a dictionary <tt>.heuristic</tt>. Nodes are just string names, but edges are dictionaries that contain each edge's <tt>"NAME"</tt>, <tt>"LENGTH"</tt>, and two endpoints, specified as <tt>"NODE1"</tt> and <tt>"NODE2"</tt>. |
The heuristic is a dictionary, for each possible goal node, mapping each possible start node to a heuristic value. | The heuristic is a dictionary, for each possible goal node, mapping each possible start node to a heuristic value. | ||
Revision as of 23:55, 21 September 2010
This problem set will be due on Friday, October 8th.
