A model of Baldwin effect in populations of self-learning agents

Author

Red, Vladimir G. ; Mosalov, Oleg P. ; Prokhorov, Danil V.

Author_Institution

Inst. of Opt. Neural Technol., Russian Acad. of Sci., Moscow, Russia

Volume

3

fYear

2005

fDate

31 July-4 Aug. 2005

Firstpage

1355

Abstract

We study an evolution model of adaptive self-learning agents. The control system of agents is based on a neural network adaptive critic design. Each agent is a broker that predicts stock price changes and uses its predictions for action selection. The agent tries to get rich by buying and selling stocks. We demonstrate that the Baldwin effect takes place in our model, viz., originally acquired adaptive policy of an agent-broker becomes inherited in the course of the evolution. In addition, we compare agent behavioral tactics with searching behavior of simple animals.

Keywords

adaptive systems; evolutionary computation; learning (artificial intelligence); multi-agent systems; neural nets; pricing; stock markets; Baldwin effect; adaptive self-learning agent; agent behavioral tactics; animal searching behavior; evolution model; neural network adaptive critic design; stock price prediction; Adaptive control; Adaptive systems; Bioinformatics; Control system synthesis; Control systems; Genetic mutations; Genomics; Neural networks; Organisms; Programmable control;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on

Print_ISBN

0-7803-9048-2

Type

conf

DOI

10.1109/IJCNN.2005.1556071

Filename

1556071