Artificial IntelligenceA revision of an established text for undergraduate and postgraduate Artificial Intelligence courses, this text incorporates the latest research and methods. |
From inside the book
Results 1-3 of 48
Page 58
... graph . This graph differs from a tree in that several paths may come together at a node . The graph corresponding to the tree of Figure 2.18 is shown in Figure 2.19 . Any tree search procedure that keeps track of all the nodes that ...
... graph . This graph differs from a tree in that several paths may come together at a node . The graph corresponding to the tree of Figure 2.18 is shown in Figure 2.19 . Any tree search procedure that keeps track of all the nodes that ...
Page 59
... graph just as for a tree . 3. If it does already exist , then do the following : ( a ) Set the node that is being ... graph . A cycle is a path through the graph in which a given node appears more than once . For example , the graph of ...
... graph just as for a tree . 3. If it does already exist , then do the following : ( a ) Set the node that is being ... graph . A cycle is a path through the graph in which a given node appears more than once . For example , the graph of ...
Page 82
... graph , several arcs may emerge from a single node , indicating a variety of ways in which the original problem might be solved . This is why the structure is called not simply an AND graph but rather an AND - OR graph . An example of ...
... graph , several arcs may emerge from a single node , indicating a variety of ways in which the original problem might be solved . This is why the structure is called not simply an AND graph but rather an AND - OR graph . An example of ...
Contents
What Is Artificial Intelligence? | 3 |
5 | 24 |
Heuristic Search Techniques | 63 |
Copyright | |
25 other sections not shown
Other editions - View all
Common terms and phrases
Abbott agents algorithm answer apply approach ARMEMPTY assertions attributes axioms backpropagation backtracking backward belief best-first search breadth-first search Caesar called Chapter chess clauses complete concept conceptual dependency consider constraints contains contradiction corresponding define depth-first depth-first search described discussed domain example fact function game tree goal grammar graph heuristic Horn clauses important inference inheritance input instance interpretation isa links John justification knowledge base knowledge representation labeled learning Marcus match minimax move MYCIN natural language node object ON(B ON(C operators output parsing particular path perceptron perform players possible preconditions predicate logic problem problem-solving procedure produce PROLOG represent result robot rules script Section semantic semantic net sentence shown in Figure simple slot solution solve specific step structure Suppose syntactic task techniques theorem things tree truth maintenance system understanding variables version space