Real World Applications

A wide range of general areas can benefit from evolutionary program adaptation such as aimed for by the BEAST project. Some of the most prominent examples include:

  1. Robotics: BEAST could be used to evolve control programs for robots, allowing them to adapt to new environments and tasks more efficiently. The virtual machine’s ability to execute bytecode efficiently and the use of genetic algorithms to optimize the control programs could make robots more autonomous and adaptable.
  2. Artificial Intelligence: BEAST could be used to evolve neural networks and other AI models, allowing them to improve over time and adapt to new data. The virtual machine’s ability to execute bytecode efficiently and the use of genetic algorithms to optimize the AI models could make AI systems more powerful and generalizable.
  3. Distributed Computing: BEAST could be used to evolve distributed computing programs, allowing them to adapt to changing network conditions and optimize for performance. The virtual machine’s ability to execute bytecode efficiently and the use of genetic algorithms to optimize the distributed computing programs could make distributed systems more resilient and efficient.
  4. Embedded Systems: BEAST could be used to evolve control programs for embedded systems, allowing them to adapt to new environments and tasks more efficiently. The virtual machine’s ability to execute bytecode efficiently and the use of genetic algorithms to optimize the control programs could make embedded systems more autonomous and adaptable.
  5. Cybersecurity: BEAST could be used to evolve programs that detect and respond to cyber threats, allowing them to adapt to new threats and improve over time. The virtual machine’s ability to execute bytecode efficiently and the use of genetic algorithms to optimize the threat detection and response programs could make cybersecurity systems more effective.

All of the above areas offer great potential for training and evolving evolutionary programs on data and interactive feedback loops. Many issues that are difficult to assess due to their complexity and potentially very challenging to encode in traditional AI systems are prime candidates for evolutionary program coding.

Specific Use-Cases

Evolving programs based on data and interactive feedback loops is a great way to prove concepts. Going from there, these programs - once reaching a proper functional basis - can be evolved into application driven expert units. Some of the relevant real world applications that potentially make sense for these programs are listed below. None of these have been pursued yet in the scope of this project, but are candidates for further investigation.

  • Creating a maze solver: A BEAST program could be evolved to navigate through a virtual maze and find its way to the exit. This could involve using sensors to detect walls, making decisions about which path to take and adapting to different maze configurations.
  • Image recognition: A BEAST program could be evolved to recognize and classify different objects in images. This could involve using convolutional neural networks and other image processing techniques.
  • Natural language processing: A BEAST program could be evolved to understand and generate natural language. This could involve using recurrent neural networks and other natural language processing techniques.
  • Game playing AI: A BEAST program could be evolved to play simple games like tic-tac-toe or more complex games like chess and Go. This could involve using decision trees and other game playing techniques.
  • Control systems: A BEAST program could be evolved to control physical systems like robots or drones. This could involve using control theory and other control techniques.
  • Financial prediction: A BEAST program could be evolved to predict financial markets or stock prices. This could involve using statistical models and machine learning techniques.
  • Medical diagnosis: A BEAST program could be evolved to diagnose diseases based on patient symptoms and medical test results. This could involve using decision trees and other medical diagnosis techniques.
  • Fraud detection: A BEAST program could be evolved to detect fraudulent activities in financial transactions. This could involve using anomaly detection techniques and machine learning algorithms.
  • Predictive maintenance: A BEAST program could be evolved to predict when equipment or machinery is likely to fail and schedule maintenance accordingly. This could involve using statistical models and machine learning techniques.
  • Energy management: A BEAST program could be evolved to optimize energy consumption in buildings or industrial plants. This could involve using control theory and other energy management techniques.