External vs. Internal Learning-by-Doing in an R&D Based Growth Model
نویسندگان
چکیده
منابع مشابه
Learning by Doing vs. Learning from Others in a Principal-Agent Model∗
We introduce learning in a principal-agent model of stochastic output sharing under moral hazard. Without knowing the agents’ preferences and technology the principal tries to learn the optimal agency contract. We implement two learning paradigms social (learning from others) and individual (learning by doing). We use a social evolutionary learning algorithm (SEL) to represent social learning. ...
متن کاملInternal vs. External Parameters in Fitness Functions
A fitness function is needed for a Genetic Algorithm (GA) to work, and it appears natural that the combination of objectives and constraints into a single scalar function using arithmetic operations is appropriate. One problem with this approach, however, is that accurate scalar information must be provided on the range of objectives and constraints, to avoid one of them from dominating the oth...
متن کاملOn the dynamics of an endogenous growth model with learning by doing∗
The paper studies the local dynamics of an endogenous growth model with externalities of investment. It is demonstrated that, in case of sustained per capita growth, the competitive economy is characterized by a situation with a unique balanced growth path which is saddle point stable or by a situation with two balanced growth paths. If there are two balanced growth paths, the one with the high...
متن کاملLearning-by-Doing in an Ambiguous Environment
CIRANO Le CIRANO est un organisme sans but lucratif constitué en vertu de la Loi des compagnies du Québec. Le financement de son infrastructure et de ses activités de recherche provient des cotisations de ses organisations-membres, d'une subvention d'infrastructure du Ministère du Développement économique et régional et de la Recherche, de même que des subventions et mandats obtenus par ses équ...
متن کاملA Cognitive Model of Learning by Doing
In this paper an approach to learning cognitive skills from problem solving experience is presented – addressing some phenomena well known from human learning but seldom covered together in machine learning. The core of our approach is the acquisition of recursive program schemes (RPSs) by generalization-to-n over plans, using an inductive program synthesis technique. RPSs represent domain spec...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SSRN Electronic Journal
سال: 1998
ISSN: 1556-5068
DOI: 10.2139/ssrn.2123679