
Udai Solanki
Project OwnerSolution Architect and Project Coordination
Blendez is a toolkit that allows concept blending developed for MeTTa in the context of Hyperon framework. It enables AGI agents to dynamically synthesize structured concepts into novel ideas, hypotheses, or action schemas. Blendez is meant to be developed as an experimental core module in PRIMUS cognitive architecture, applying Formal Concept Analysis (FCA) and its fuzzy extensions.
This RFP seeks proposals that experiment with concept blending techniques and formal concept analysis (including fuzzy and paraconsistent variations) using the MeTTa programming language within OpenCog Hyperon. The goal is to explore methods for generating new concepts from existing data and concepts, and evaluating these processes for creativity and efficiency. Bids are expected to range from $30,000 - $60,000.
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Summarize the techniques related to blending which includes symbolic fuzzy and paraconsistent formal concept analysis evaluating their usefulness for blending. Formulate the rationale and technique for implementing blending in MeTTa. Construct the design of a modular blending engine for MeTTa expressions that can be Hyperon framework compatible and plugins for blending. Create an intricate roadmap that includes a milestone-criteria checklist for evaluation metrics of creativity uniqueness and logical coherence.
Research Plan: MeTTa encoding models and main techniques including a model outcomes analysis in a PDF document. Technical Design Document: outlines the software architecture the symbolic data schemas the API designs and the plans themselves. Task Timeline: allocates all development phases and works towards an agile detailed roadmap. Optional: Reference examples of concept blending encoded in MeTTa for benchmarking.
$6,000 USD
Research Plan Clearly explains MeTTa encoding models and symbolic representation techniques and it includes a comprehensive review of relevant literature and prior work. Presents a clear and modular software architecture using diagrams and document API A development plan which Includes start and end dates, dependencies, and milestone checkpoints. At least 2 concept blending examples are encoded and validated in MeTTa
Objectives: - Implementing the Blendez core engine: - Symbolic Blend Operators for Logically Fusing Concepts - Blending Under Uncertainty with Fuzzy and Paraconsistent Extensions. Workflows configuration and inspection for blending through MeTTta scripts will be set with command line interfaces: Preliminary benchmarks of symbolic consistency novelty and utility alongside a controlled data set such as domain-specific concept maps or ontologies will run for evaluation during this stage: Begin documenting patterns for development in the MeTTa API.
Modular blending strategies for Blendez and concept blending sessions both on a MeTTa-based prototype documents under construction: Calculated benchmarks on toy ontologies and logical predicates named benchmark concept sets. Blending CBLing and inspection through a CLI for concept sessions. Evaluation notes reshaping blending heuristics: symbolic fuzzy and paraconsistent. Draft API reference alongside a guide for developer usage.
$12,000 USD
Multiple blending strategies are implemented (e.g., symbolic, analogical, structural). Strategies are modularized: Clear interfaces for plugging in/out specific blending modules. Strategy logic is reusable across different concept domains. At least 3 documented concept blending sessions: With traceable MeTTa input code and outcome artifacts. Showing before/after states of blended concept spaces. Benchmark results are: Quantified using blending success metrics (novelty, coherence, usefulness). Documented and visualized (e.g., tables, plots). Provides a command-line interface (CLI) that: Launches new blending sessions. Accepts MeTTa input or loads predefined sets. Displays session logs and intermediate results. Evaluation notes cover: What worked, what failed, and why (with examples). Provides a draft API reference: Core functions, classes, endpoints. Example input/output for each method.
Objectives: Put the toolkit through polishing and modification under the condition that modularity and integration readies Hyperon Create a simple web viewer with React or static JS that will visualize entries and results of concept structures. Make sure it works with the Atomspace/MORK backend for symbolic storage and evaluation. Complete documentation should be published while the framework can be open-sourced under AGPL/GPL license. Deliver a short demonstration video along with a final walkthrough for the use case.
Final code repository: Blendez engine + UI + docs Terms of the open-source license and its usage. MeTTa scripts and test cases provided for efficient reuse. APIs overviews along with guide and manual for setup installation and use. Demo of integration showcasing how Blendez blends can be incorporated into Atomspace or PRIMUS. A report that consolidates technical outcomes performance insights and challenges and proposed recommendations for the project’s further advancement.
$12,000 USD
Final Code Repository Contains well-organized code for Blendez engine, UI, and documentation. Passes all tests and includes README with clear instructions. Maintains consistent structure and style. Open-Source Licensing Includes a valid open-source license file (e.g., MIT, Apache 2.0). Clearly states terms of use, contributions, and distribution. MeTTa Scripts & Test Cases Provides reusable MeTTa scripts for core blending tasks. Includes automated and manual test cases with expected outcomes. API Overview & User Guide Documented API with endpoint/function descriptions. Setup, installation, and usage instructions in a step-by-step guide. Integration Demo Demonstrates successful integration with Atomspace or PRIMUS. Shows end-to-end blending in the target system context. Technical Report Summarizes performance results, insights, and encountered challenges. Offers actionable recommendations for future development. Includes diagrams, examples, and performance metrics where applicable.
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