This milestone focuses on the development of foundational MeTTa scripts to adapt AI behavior based on emotional states. We will create modular reusable scripts that map emotions (happiness sadness focus and stress) to AI responses. This phase will involve initial prototyping of the adaptive response system ensuring its readiness for integration with EEG emotion detection systems. 1. Design and develop MeTTa scripts for predefined emotional states. 2. Prototype core functionality demonstrating AI response generation based on static emotional inputs. 3. Create modular frameworks that allow future integration with dynamic data sources like EEG. 4. Begin drafting documentation to describe script functionality and modularity for developers.

1. Functional MeTTa scripts capable of simulating AI behavior for predefined emotional states. 2. Modular framework for adaptable AI behavior. 3. Draft documentation detailing the script architecture and use cases.

$6,000 USD

1. Developed MeTTa scripts simulate predefined emotional states (happiness, sadness, focus, stress) with appropriate AI responses. 2. Core functionality is successfully prototyped, showcasing accurate AI response generation based on static emotional inputs. 3. Initial draft documentation clearly describes the script architecture, modularity, and use cases, making it accessible to developers.

This milestone involves integrating the existing EEG-based emotion classification model with the MeTTa framework. The primary goal is to enable real-time emotional data to dynamically drive the behavior of AI companions. Rigorous testing and validation will ensure seamless communication between the emotion model and MeTTa scripts while the modular design will allow easy replication and customization. 1. Develop a robust data pipeline connecting the EEG emotion classification API with MeTTa. 2. Implement triggers in MeTTa scripts to adapt AI behavior dynamically based on real-time emotional inputs. 3. Validate system performance through end-to-end testing of real-time emotional adaptations. 4. Refine the integration framework based on test results ensuring smooth interaction and minimal latency.

1. Integrated data pipeline for real-time emotional state inputs. 2. Validated system demonstrating real-time adaptability based on EEG data. 3. Modular integration examples showcasing behavior triggering.

$10,000 USD

1. MeTTa scripts dynamically adapt AI behavior based on real-time emotional state changes. System successfully passes end-to-end testing, demonstrating smooth interaction, minimal latency, and accurate emotional response adaptation. 2. Real-time adaptability to various EEG-detected emotional states is successfully demonstrated.

The final milestone focuses on deploying the complete emotion-adaptive AI system on a SingularityNET Hyperon instance. This includes final testing demonstration and the release of open-source components ensuring the community can replicate and extend the project. Comprehensive documentation will provide step-by-step instructions for setup customization and integration into other applications. 1. Deploy the fully functional AI system on Hyperon including real-time emotional adaptation. 2. Conduct final testing and validation to ensure robustness and scalability. 3. Prepare open-source documentation with detailed guides examples and best practices. 4. Release modular MeTTa scripts and integration frameworks in a public repository. 5. Create demonstration scenarios showcasing the AI’s ability to respond empathetically to emotional states.

1. Deployed AI companion system demonstrating real-time emotion adaptation. 2. Open-source repository with clean well-commented MeTTa scripts and modular integration examples. 3. Comprehensive documentation covering setup usage and customization for developers. 4. Demo scenarios to encourage adoption and replication.

$9,000 USD

1. The emotion-adaptive AI system is deployed on SingularityNET Hyperon, functioning reliably with real-time emotional adaptation. 2. Public repository contains clean, well-documented, and modular MeTTa scripts along with integration frameworks. 3. Demonstration scenarios effectively showcase AI’s empathetic responses to emotional states, encouraging community adoption and replication.