|
|
|
|
|
Leader |
LDR
|
|
cam a 00 |
|
Control # |
1
|
|
hbl99064346 |
|
Control # Id |
3
|
|
GCG |
|
Date |
5
|
|
20200515112533.0 |
|
Fixed Data |
8
|
|
951227s1996 caua b 000 0 eng |
|
LC Card |
10
|
|
$a 95050246 |
|
ISBN |
20
|
|
$a0803972709 (pbk. : acid-free paper) |
|
Obsolete |
39
|
|
$a292300$cTLC |
|
Cat. Source |
40
|
|
$aDLC$cDLC$dDLC$dGCG |
|
LC Call |
50
|
00 |
$aH61$b.T237 1996 |
|
Dewey Class |
82
|
00 |
$a003/.3$220 |
|
ME:Pers Name |
100
|
1 |
$aTaber, Charles S. |
|
Title |
245
|
10 |
$aComputational modeling /$cCharles S. Taber, Richard J. Timpone. |
|
Imprint |
260
|
|
$aThousand Oaks, Calif. :$bSage Publications,$cc1996. |
|
Phys Descrpt |
300
|
|
$aviii, 95 p. :$bill. ;$c22 cm. |
|
Series:Diff |
490
|
0 |
$aSage University papers series - Quantitative applications in the social sciences ;$vv. 07-113 |
|
Note:Bibliog |
504
|
|
$aIncludes bibliographical references (p. 89-93). |
|
Note:Content |
505
|
0 |
$aIntroduction: Beyond platforms and on-ramps. Models and computational models. Why model computationally? Where is computational modeling likely to be most useful? Drawbacks of computational modeling. General stages in a computational modeling project. An overview of the following chapters -- Dynamic simulation models: Dynamic simulation. Cellular automata -- Knowledge-based systems: Semantic networks. Frame systems. Rule-based expert systems. Hybrid systems. -- Models of machine learning: Connectionist models. ID3. Genetic algorithms -- Evaluating computational models: Truth. Beauty. Justice. Conclusion. |
|
Subj:Topical |
650
|
0 |
$aSocial sciences$xMathematical models. |
|
Subj:Topical |
650
|
0 |
$aSocial sciences$xData processing. |
|
AE:Pers Name |
700
|
1 |
$aTimpone, Richard J. |
|
SE:Ufm Title |
830
|
0 |
$aSage University papers series - Quantitative applications in the social sciences ;$vv. 07-113. |
