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4ПРОЕКТИРОВАНИЕ ИНТЕЛЛЕКТУАЛЬНЫХ АГЕНТОВ ОСНОВАННЫХ НА ЛОГИЧЕСКИХ СХЕМАХ С ПОМОЩЬЮ АЛГОРИТМА _ГЕНЕТИЧЕСКОГО ПРОГРАММИРОВАНИ_
Казанцева Юлия Валерьевна
Магистр
Сибирский Государственный аэрокосмический университет имени академика М. Ф. Решетнева, г. Красноярск Липинский Леонид Витальевич кандидат тех. наук, доцент Сибирский Государственный аэрокосмический университет имени академика М. Ф. Решетнева, г. Красноярск Карчава Ольгап Витальевна старший преподаватель Сибирский Государственный аэрокосмический университет имени академика М. Ф. Решетнева, г. Красноярск
INTELLIGENT AGENTS DESIGN BASED ON THE LOGIC CIRCUIT BY MEANS OF THE
GENETIC PROGRAMMING.
Kazantseva Yyliya
Master's degree Reshetnev Siberian State Aerospace University.
Krasnoyarsk Lipinsky Leonid
Candidate of Engineering Sciences, assistant professor Reshetnev Siberian State Aerospace University.
Krasnoyarsk Karchava Olga Senior teacher
Reshetnev Siberian State Aerospace University.
Krasnoyarsk
АННОТАЦИЯ
В данной работе предложен метод проектирования интеллектуальных агентов, основанных на логических схемах при помощи генетического программирования.
ABSTACT
In this paper method of designing intelligent agents based on logic circuits, using genetic programming is suggested.
Ключевые слова: интеллектуальные агенты, интеллектуальные технологии Keywords: intelligent agents, genetic programming, logic circuits.
Intelligent information technologies (SIT) are In the field of Artificial Intelligence this is called
successfully applied for a wide range of practical tasks an "intellectual essence" (software) [4], acquiring in-[3]. Intelligent agents are one of the recent break- formation about the outer environment, the current throughs in IIT(, intended to solve different problems processes and their results through the system of sen-without a human. Initially, all the possible sequences sors, and having an access to the management through of actions have to be created by a developer and in- the actuator system. The behavior of the agents is tar-stalled into the intelligent agents. In case such system geted at a certain aim [1]. A scheme of such agent is faces conditions that haven't been considered by the presented in Figure 1.
creator, the system may crash or even fail.
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17
Figure 1. Interaction of the intellectual agent between the environment.
One of the agent development methods is forming an agent with the help of logical schemes (Fig.2). In this case the agent has a list of formal logic statements, describing the causal relationship in the envi-
Events
ronment and possible changes in it that can be caused by the agent's actions, interpreted at a current state of environment as a true one, on the assumption that the agent has performed the corresponding action.
Actions
A
1
c > - ^ ^ 3
D 4
Figure 2. An example of a generalized logical scheme of the agent.
For the automatic formation of the agent through the genetic programming the agent should be rendered into a tree [2]. For this task it is convenient to render an individual into a set of trees (as it is depicted in Fig.3). Each tree is responsible for one particular decision, based on one action. Each individual includes the
number of trees equal to the number of actions one agent can perform. The functional open set of the agent includes such logical operators as AND, OR, NAND and negation. The terminal set consists of all the events that the agent can detect and register.
2
Action 1
Figure 3. The conception of an individual
The distinctive feature of the algorithm is the fact that the main evolutional operators, such as initiation, breeding and mutation will work with the genotype, presented not by one tree, but by several ones. This causes not alteration in the flow of initiation and mutation processes. However, in the process of breeding genetic code exchange occurs only between those trees that comply with the same actions. Applicability assessment is conducted within the agent environment functioning model. Agent is supplied with the necessary resources on functioning and a logical scheme on the basis of the estimated individual is formed. As the agent finishes all operations, the efficiency of its performance is evaluated and the agent is declared applicable or inapplicable for the evolutional algorithm.
The application of genetic programming for intelligent agents' development and optimization is proba-
ble to optimize both the time of agent development and the efficiency of their usage. The intellectual agent development method has a wide range of application spheres from computer games to unmanned vehicle control.
Reference list
1. Bugaytshenko D.Y., Solovyev I.P. Abstract intelligent agent architecture and its realization methods. 2005.
2. Lipinsky L.V. Semyonkin E.S. Automation of intelligent information technologies design through genetic programming method. Fizmatlit, 2006.
3. Lipinsky L.V. Semyonkin E.S. Genetic programming algorithms for intellectual information technologies formation. Krasnoyarsk 2006.
4. Rassel S. Norwig P. Artificial Intelligence: modern approach. Williams. 2006. S 282-331
МАТЕМАТИЧЕСКАЯ МОДЕЛЬ ВЫБОРА МОТОРНОГО МАСЛА ПО ТЕКУЩЕМУ ТЕХНИЧЕСКОМУ СОСТОЯНИЮ ДВИГАТЕЛЯ, ОПРЕДЕЛЯЕМОГО ПО СПЕКТРАЛЬНОМУ АНАЛИЗУ РАБОТАЮЩЕГО _МАСЛА_
Белик Александр Александрович
Инженер, ООО «Автотема» г. Новосибирск Ломухин Владимир Борисович кандидат техн. наук, доцент Сибирский государственный университет водного транспорта,
г. Новосибирск Лаптева Ирина Владимировна Старший преподаватель
Новосибирский государственный архитектурно-строительный университет (СИБСТРИН),
г. Новосибирск
