Flow-guided scientific research and creative evolution generation method, electronic device and computer readable storage medium
By employing a flow-guided method for generating research ideas through evolution, and combining literature knowledge graphs and Monte Carlo tree search, the retrieval path is dynamically adjusted and ideas evolve. This approach addresses the issues of information source diversity and idea quality in the generation of research ideas, and achieves interdisciplinary integration and quality improvement of ideas.
Patent Information
- Authority / Receiving Office
- CN Β· China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- DALIAN UNIV OF TECH
- Filing Date
- 2026-03-31
- Publication Date
- 2026-07-03
AI Technical Summary
Existing scientific research idea generation technologies suffer from several problems, including a one-way separation between the retrieval and generation processes, limited diversity of information sources, low quality of the initial idea population, and difficulty in effectively balancing the novelty and feasibility of ideas.
We adopt a flow-guided scientific research idea evolution generation method. By constructing a multidisciplinary literature knowledge graph, combining Monte Carlo tree search and generative reward evaluation, we dynamically adjust the retrieval path and introduce cross-domain information during the idea evolution process to perform cross mutation operations to optimize idea quality.
It achieves bidirectional collaborative evolution of the retrieval and generation processes, expands the diversity of information sources, enhances the interdisciplinary integration capability and quality of creative ideas, dynamically improves the novelty and feasibility of creative ideas, and solves the limitations of existing technologies.
Smart Images

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