Development of a foundational system for efficient incremental updates to knowledge graphs without full rebuilds. This milestone will deliver a working prototype of our delta encoding and change log mechanism that dramatically reduces storage requirements while preserving historical information. The system will implement distributed incremental update algorithms capable of processing changes in parallel across large-scale knowledge graphs.

- Functional prototype of the delta encoding system with documented API for integrating new knowledge - Technical documentation detailing the architecture and implementation of the incremental update algorithms

$25,000 USD

The system demonstrates significant reduction in computational resources required for knowledge updates compared to full-graph regeneration approaches, while maintaining query performance. The prototype successfully processes incremental updates on graphs with at least million nodes and edges.

Implementation of a comprehensive version control system specifically designed for knowledge graphs. This milestone will deliver a layered architecture that stores initial graph state in a base layer with subsequent updates as delta layers. The system will provide branch and merge capabilities, enabling experimental knowledge paths without affecting the main graph.

- Complete version control system with branching, merging, and rollback capabilities - Query interface that enables temporal navigation across different graph states

$30,000 USD

The system successfully maintains and provides access to the versions of a knowledge graph with minimal storage overhead. Users can efficiently query any historical state of the graph.

Implementation of sophisticated mechanisms for detecting and resolving conflicts when merging knowledge from multiple sources. This milestone will deliver conflict detection based on logical consistency checking and probabilistic reasoning with confidence scoring. It will also implement advanced conflict resolution strategies considering source reliability, temporal context, and semantic relationships.

- Conflict detection engine capable of identifying logical inconsistencies across merged knowledge graphs - Resolution framework supporting multiple strategies including rule-based, probabilistic, and hybrid approaches - Case study demonstrating successful conflict resolution in a complex domain with multiple knowledge sources - Entity resolution engine with configurable matching strategies and threshold settings

$25,000 USD

The system accurately identifies at least 80% of intentionally introduced conflicts in test datasets. Resolution strategies successfully resolve at least 75% of complex conflicts (involving temporal constraints, uncertain information, or schema differences) without human intervention.

Seamless integration of our dynamic knowledge graph framework with the Metta/MORK system to enhance real-time reasoning and retrieval capabilities. This milestone will deliver adapter components and API mappings that enable our versioning and incremental update capabilities to work directly with Metta/MORK's symbolic inference engine.

- Complete set of adapter components enabling bidirectional communication between our framework and Metta/MORK - Extended query language supporting temporal and versioned knowledge retrieval within the Metta/MORK environment - Comprehensive documentation and examples showcasing integrated workflows for common reasoning tasks

$7,500 USD

The integrated system demonstrates successful execution of at least 2-3 complex reasoning scenarios requiring both dynamic knowledge updates and symbolic inference.