1.8 KiB
1.8 KiB
Research-Swarm - Distributed Research Collaboration
Overview
Distributed research graph with collaborative literature review, hypothesis generation, experimental validation, and knowledge synthesis.
Purpose
Model how multiple research agents can collaborate on scientific research through shared knowledge graphs.
Operations
- Papers Reviewed: 5 (literature search)
- Hypotheses Generated: 3 (synthesis)
- Experiments Conducted: 3 (validation)
- Synthesized Knowledge: 3 research methods
Results
- Throughput: 2.01 ops/sec
- Latency: 486ms avg
- Papers Reviewed: 5
- Hypotheses: 3
- Experiments: 3
- Research Methods: 3
- Confirmation Rate: 67% (2/3 confirmed)
Technical Details
Research Workflow
1. Literature Review
├── Agent 0: Neural architecture search
├── Agent 1: Few-shot learning methods
└── Agent 2: Transfer learning strategies
2. Hypothesis Generation
└── Synthesize insights from papers
→ "Combining meta-learning with architecture search
improves few-shot performance"
3. Experimental Validation
└── Test hypothesis
→ Result: Confirmed (92% confidence)
4. Knowledge Synthesis
└── Create reusable research method
→ "meta_architecture_search_protocol"
Causal Links
Papers → Hypotheses (support relationships) Hypotheses → Experiments (validation links)
Applications
- Academic Research: Literature meta-analysis
- Drug Discovery: Hypothesis generation
- Materials Science: Property prediction
- AI Research: AutoML and architecture search
Research Capabilities
- Collaborative literature review
- Hypothesis generation from synthesis
- Experimental design and validation
- Method reusability and composition
Status: ✅ Operational | Package: research-swarm