Borhan Pie Reasoner
Pie Reasoner
(Platform-independent, Incremental and Expandable reasoner)
Machine reasoning plays a crucial role in various fields, offering a coherent, consistent, and adaptable structure for knowledge processing. It enables the discovery of new logical outcomes, making it valuable in domains like bioinformatics, knowledge management, medicine, pharmaceuticals, legal judgment, and insurance. Additionally, automatic reasoners are essential components in expert and robotic systems.
We have published an article about the importance of using automated reasoning in another post.
This post introduces Pie Reasoner, a platform-independent, incremental, and expandable automated reasoning engine:
Platform-Independent Reasoning:
Pie is a portable reasoner that operates seamlessly across different operating systems, databases/knowledgebases, and hardware. Its core functionality is independent of specific software environments, programming languages, or operating systems (Windows, Mac, Linux, etc.). This platform independence offers significant advantages in adaptability and flexibility.
- Effortless Integration: Use the same logic across different machines or integrate it into various programs without rewriting the original code.
- Simplified Maintenance: Updates and bug fixes can be applied centrally, simplifying maintenance since the core logic is separate from the platform.
- Database Adaptability: Pie adapts to different databases/knowledgebases, including RDF/Triple Stores (SPARQL query language), Neo4j, and even SQL/NoSQL structures. Existing data can be easily integrated.
Incremental Reasoning:
Incremental reasoning continuously updates knowledge and conclusions as new information arrives. This contrasts with traditional reasoning, which requires all initial knowledge upfront before processing and generating conclusions. In incremental reasoning, new information is fed to the reasoner piece by piece, allowing for continuous updates and understanding.
Benefits of Incremental Reasoning:
- Real-Time Capability: Reasoners can operate in dynamic environments where results based on new information need to be continuously available. This is crucial for applications like robotics and medical diagnostics where real-time decision-making is critical.
- Efficiency: The reasoner only processes new information, avoiding re-analysis of everything from scratch with each update, leading to high efficiency.
- Scalability: Reasoning only focuses on changes and new information, even with large knowledge graphs. After reaching a fixed point, the reasoning remains efficient regardless of the size of the databases/knowledgebases.
- Hardware Flexibility: Reasoning can continue on new hardware even after changes or inconsistencies are discovered, allowing for processor or hardware changes without interruption.
Expandable Reasoning:
Currently, no universal reasoner handles all possible logics, such as temporal-dynamic logic or prioritized default logic. Non-classical logic reasoners are necessary when dealing with domains with limited information or knowledge that changes based on events.
Pie’s infrastructure supports nested logic and hybrid reasoning between extensions of description logic. It currently offers:
- Prioritized default reasoner for non-monotonic reasoning
- Temporal dynamic reasoner for managing action-induced changes over time
- Abductive reasoner for making the best possible guess based on available information
Pie’s infrastructure allows for the addition of custom logic extensions like probabilistic logic, with rules written based on the selected database (e.g., SPARQL/SPIN for RDF, Cypher for Neo4j, MQL for MongoDB). Pie even facilitates seamless transitions between different description logic forms, like ALC to SHOIN and vice versa. Additionally, users can leverage SHACL functionalities when using the RDF structure.
Using Pie Reasoner:
Pie Reasoner is incredibly user-friendly. Simply provide changes in OWL-Functional syntax. To order the service, send a request to product@borhan-onto.ir .
Test Pie’s performance with your data and Borhan Pie’s support team will be happy to assist you.
We look forward to hearing from you!