2. Development of mathematical models for control function synthesis based on symbolic regression and evolutionary methods Measurable indicators: Creation and formalization of control models for mobile and autonomous robots. Role in the project: This task is focused on building the core mathematical model for developing intelligent control systems, ensuring adaptability and efficiency in response to the robot’s state and environment.

3. Investigation of variational programming methods for automatic control function generation Measurable indicators: Implementation and testing of variational algorithms for control function creation. Role in the project: Variational methods will enable efficient search for optimal control functions, reducing resource and time costs, thus enhancing control system performance.

4. Development of algorithms for multi-agent coordination of autonomous robots Measurable indicators: Creation of interaction and coordination algorithms for multiple robots. Role in the project: Effective coordination in multi-agent systems will improve the collaborative work of robots, crucial for tasks like monitoring or joint operations.

5. Optimization of control algorithms using machine learning methods Measurable indicators: Development and testing of machine learning algorithms to improve control systems’ accuracy and adaptability. Role in the project: Machine learning will enhance control decisions, helping robots adapt to dynamic conditions and predict environmental changes.

6. Testing and verification of developed control systems in simulation and real-world scenarios Measurable indicators: Conducting tests in various scenarios, evaluating system effectiveness. Role in the project: This task will validate the proposed solutions, demonstrating system performance under uncertainty and external disturbances.
Each task is logically connected to the project’s goal—developing intelligent control systems for robots using evolutionary methods and AI, achieving high adaptability and efficiency in real conditions.

1) Planned publications:
At least 2 (two) articles and/or reviews will be published in peer-reviewed scientific journals in the field of the project, indexed in the Science Citation Index Expanded and included in the 1st, 2nd, and/or 3rd quartiles by impact factor in the Web of Science database and/or with a percentile of at least 50 (fifty) in the CiteScore of the Scopus database.
At least 1 (one) article or review in a peer-reviewed foreign or domestic journal recommended by the KKSONVO.

2) The publication of monographs, books, and/or chapters in books by foreign and/or Kazakhstani publishers is not planned;

3) Patents for inventions and/or utility models in the Republic of Kazakhstan are not planned;

4) Development of scientific-technical or design documentation is not planned;

5) The dissemination of results to potential users, the scientific community, and the general public will be carried out through publications in scientific and popular science journals, relevant internet portals, participation in conferences, exhibitions, and seminars.

The developed intelligent control systems are expected to find applications in various fields, including:
Agriculture: Autonomous robots will be able to perform tasks such as monitoring, harvesting, and soil cultivation, increasing productivity and reducing labor costs.
Industry: The developed systems will be used to automate processes in logistics and production, improving efficiency and reducing the risk of human error.
Ecology and environmental monitoring: Robots with autonomous control systems will be able to carry out tasks for monitoring the environment, including the analysis of soil, water, and air in remote and hard-to-reach areas.
Commercialization of the project results is possible through the creation of startups or licensing developments to industrial and agricultural companies interested in process automation. This will create an economic effect by reducing production costs and improving productivity in key industries.

The social impact of the project lies in the development of Kazakhstan's scientific potential in the field of robotics and artificial intelligence. The training of highly qualified specialists and the publication of results on international platforms will strengthen the country's scientific position and its competitiveness in high-tech industries.

The project will also have a multiplier effect on related fields of science and technology, including the development of new methods in artificial intelligence and data processing. The environmental impact may be achieved through the use of autonomous robots for environmental monitoring and addressing ecosystem protection challenges.