Proceedings of the 2016 Conference on Information Technologies in Science, Management, Social Sphere and Medicine

Decision-Making by Agents with Endogenous Aims Using Genetic Algorithm

Authors
Gennadiy Vinogradov, Nataliya Vinogradova
Corresponding Author
Gennadiy Vinogradov
Available Online May 2016.
DOI
https://doi.org/10.2991/itsmssm-16.2016.20How to use a DOI?
Keywords
choice model,fuzzy evaluations, modeling, purposeful systems, situation control
Abstract
The problem of constructing a choice model of an agent endogenously shaping purposes of his evolution is under debate. It is demonstrated that its solution requires the development of well-known methods of decision-making while taking into account the relation of action mode motivation to an agent's ambition to implement subjectively understood interests and the environment state. The latter is submitted for consideration as a purposeful state situation model that exists only in the mind of an agent. It is the situation that is a basis for getting an insight into the agent's ideas on the possible selected action mode results. The agent's ambition to build his confidence in the feasibility of the action mode and the possibility of achieving the desired state requires him to use the procedures of forming a model-representation based on the measured values of the environment state. This leads to the gaming approach for the choice problem and its solution can be obtained on a set of trade-off alternatives.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
Information Technologies in Science, Management, Social Sphere and Medicine
Part of series
Advances in Computer Science Research
Publication Date
May 2016
ISBN
978-94-6252-196-4
ISSN
2352-538X
DOI
https://doi.org/10.2991/itsmssm-16.2016.20How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Gennadiy Vinogradov
AU  - Nataliya Vinogradova
PY  - 2016/05
DA  - 2016/05
TI  - Decision-Making by Agents with Endogenous Aims Using Genetic Algorithm
BT  - Information Technologies in Science, Management, Social Sphere and Medicine
PB  - Atlantis Press
SP  - 93
EP  - 99
SN  - 2352-538X
UR  - https://doi.org/10.2991/itsmssm-16.2016.20
DO  - https://doi.org/10.2991/itsmssm-16.2016.20
ID  - Vinogradov2016/05
ER  -