Functional Requirements

Must have

• Core motivational framework design
  • Develop a modular, extensible framework that can be used with Hyperon components such as ECAN, DAS, and MeTTa.
  • Enable dynamic adjustment of motivational priorities based on internal states and external factors.
  • Ensure alignment with human values and socially beneficial outcomes.

• Detailed use cases
  • Provide a detailed explanation of how the given motivation framework would display itself in some concrete use-cases including: chatbot systems, and one or both of:
    • humanoid robots
    • or virtual agents / neoterics, such as in a metaverse environment like Sophiaverse 
• Efficiency of execution
  • Ensure the framework is designed for efficient performance in real-time environments. We wouldn't want a framework that is slow, even if it is scalable. We want implementations using the framework to be used in games, or other virtual worlds.
• Scalability and adaptability
  • Consider scalability from simple tasks to advanced AGI applications, supporting both low-complexity environments (e.g., simulations) and high-complexity AGI systems.

Should have

• Human-like as well as alien motivations
  • Support the creation or implementation of both human-like and non-human ("alien digital") motivational structures, adaptable to diverse AGI systems.
• Real-time adaptability
  • Ensure the system or framework can dynamically adjust motivational priorities in real-time, especially in rapidly changing environments like virtual worlds.
• Ethical alignment mechanism
  • Provide or guide the development of a flexible mechanism for governing motivations by ethical principles, ensuring socially responsible behavior.
• Customizable motivational systems
  • Allow for easy configuration and customization of motivational models, facilitating experimentation and adaptation to various AGI contexts.

Could have

• Cross-domain applicability
  • Apply or provide conceptual guidance for applying the framework across different domains, from virtual worlds to real-world robotic systems and beyond.
• Support for sub-symbolic systems
  • Optionally support or provide a basis for integrating sub-symbolic motivational approaches like neural networks or reinforcement learning.

Won’t have (yet)

• Complex emotional simulation
  • The framework will not focus on simulating complex emotions at this stage, leaving room for future exploration.
• Autonomous ethical rule generation
  • The framework will not autonomously generate ethical rules but will adhere to or guide predefined ethical standards.