Neural voting machines

被引:6
作者
Richards, Whitman
Seung, H. Sebastian
Pickard, Galen
机构
[1] MIT, CSAIL, Cambridge, MA 02139 USA
[2] MIT, Dept Brain & Cognit Sci, Cambridge, MA 02139 USA
[3] MIT, Howard Hughes Med Inst, Cambridge, MA 02139 USA
关键词
information aggregation; social networks; decision-making; winner-take-all; Borda Count; Condorcet voting; domain knowledge; neuroeconomics;
D O I
10.1016/j.neunet.2006.06.006
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A "Winner-take-all" network is a computational mechanism for picking an alternative with the largest excitatory input. This choice is far from optimal when there is uncertainty in the strength of the inputs, and when information is available about how alternatives may be related. For some time, the Social Choice community has recognized that many other procedures will yield more robust winners. The Borda Count and the pair-wise Condorcet tally are among the most favored. If biological systems strive to optimize information aggregation, then it is of interest to examine the complexity of networks that implement these procedures. We offer two biologically feasible implementations that are relatively simple modifications of classical recurrent networks. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1161 / 1167
页数:7
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