The Hare and the Tortoise: Network structure in collaborative problem solving
نویسندگان
چکیده
Policy makers often face similar problems, and tackling them is often a social effort, where individuals can share information through network ties about how to solve the problems they face. In particular, it has been amply documented that actors tend to emulate successful others that they observe. We present a simulation demonstrating that more efficient communication can actually lower total performance in the long run. This effect is manifest in complex (e.g. rugged) problem spaces, where extensive searches are expensive for the individual. When actors can communicate easily, average performance improves initially, but harder-to-find optimal solutions are less likely to be discovered. Small-world networks and cliques in communication have important implications for the social outcomes in a collaborative network.
منابع مشابه
Conversion of Network Problem with Transfer Nodes, and Condition of Supplying the Demand of any Sink from the Particular Source to the Transportation Problem
In this article we present an algorithm for converting a network problem with several sources and several sinks including several transfer nodes and condition of supplying the demand of any sink from a particular source to the transportation problem. Towards this end, and considering the very special structure of transportation algorithm, after implementing the shortest path algorithm or ...
متن کاملAn efficient one-layer recurrent neural network for solving a class of nonsmooth optimization problems
Constrained optimization problems have a wide range of applications in science, economics, and engineering. In this paper, a neural network model is proposed to solve a class of nonsmooth constrained optimization problems with a nonsmooth convex objective function subject to nonlinear inequality and affine equality constraints. It is a one-layer non-penalty recurrent neural network based on the...
متن کاملA Recurrent Neural Network for Solving Strictly Convex Quadratic Programming Problems
In this paper we present an improved neural network to solve strictly convex quadratic programming(QP) problem. The proposed model is derived based on a piecewise equation correspond to optimality condition of convex (QP) problem and has a lower structure complexity respect to the other existing neural network model for solving such problems. In theoretical aspect, stability and global converge...
متن کاملA Recurrent Neural Network Model for solving CCR Model in Data Envelopment Analysis
In this paper, we present a recurrent neural network model for solving CCR Model in Data Envelopment Analysis (DEA). The proposed neural network model is derived from an unconstrained minimization problem. In the theoretical aspect, it is shown that the proposed neural network is stable in the sense of Lyapunov and globally convergent to the optimal solution of CCR model. The proposed model has...
متن کاملA model for distribution centers location-routing problem on a multimodal transportation network with a meta-heuristic solving approach
Nowadays, organizations have to compete with different competitors in regional, national and international levels, so they have to improve their competition capabilities to survive against competitors. Undertaking activities on a global scale requires a proper distribution system which could take advantages of different transportation modes. Accordingly, the present paper addresses a location-r...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2005