Do evolutionary processes minimize expected losses?

نویسندگان

  • D B Fogel
  • H G Beyer
چکیده

Evolution by variation and natural selection is often viewed as an optimization process that favors those organisms which are best adapted to their environment. This leaves open the issue of how to measure adaptation and what criterion is implied for optimization. This problem has been framed and analysed mathematically under the assumption that individuals compete to minimize expected losses across a series of decisions (e.g. choice of behavior), where each decision offers a stochastic payoff. But the fact that a particular analysis is tractable for a specified criterion does not imply the fidelity of that criterion. Computer simulations involving a version of the k -armed bandit problem can address the veracity of the hypothesis that individuals are selected to minimize expected losses. The results offered here do not support this hypothesis.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Time-related issues with application to health gains and losses.

Time-related aspects of health have attracted increasing interest, and it has become evident that many medical situations concern the exchange of present-day costs for future benefits. Traditional decision analytic paradigms weigh the probability of outcomes and the value of outcomes. Such analyses are incomplete if they do not consider the time of the outcome as well. The concept of diminishin...

متن کامل

Prediction of Surface Roughness by Hybrid Artificial Neural Network and Evolutionary Algorithms in End Milling

Machining processes such as end milling are the main steps of production which have major effect on the quality and cost of products. Surface roughness is one of the considerable factors that production managers tend to implement in their decisions. In this study, an artificial neural network is proposed to minimize the surface roughness by tuning the conditions of machining process such as cut...

متن کامل

An Evolutionary Multi-objective Discretization based on Normalized Cut

Learning models and related results depend on the quality of the input data. If raw data is not properly cleaned and structured, the results are tending to be incorrect. Therefore, discretization as one of the preprocessing techniques plays an important role in learning processes. The most important challenge in the discretization process is to reduce the number of features’ values. This operat...

متن کامل

Reducing Losses in a Deregulated Power System with Teaching Learning Based Optimization Algorithm

The robust Newton–Raphson method is suggested to solve the power flow equations. Newton power flow algorithms do not automatically minimize objective function such as real power losses. Hence, this paper presents teaching learning based optimization (TLBO) approach to minimize power lossesby the optimal allocation of reactive power sources considering placement and value in restructured power s...

متن کامل

An Evolutionary Method for Improving the Reliability of Safetycritical Robots against Soft Errors

Nowadays, Robots account for most part of our lives in such a way that it is impossible for usto do many of affairs without them. Increasingly, the application of robots is developing fastand their functions become more sensitive and complex. One of the important requirements ofRobot use is a reliable software operation. For enhancement of reliability, it is a necessity todesign the fault toler...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Journal of theoretical biology

دوره 207 1  شماره 

صفحات  -

تاریخ انتشار 2000