The invention discloses a dynamic arrangement and iterative optimization method for a skill map in the water conservancy field, and relates to the technical field of
artificial intelligence and
informatization. Comprising the steps of 1, performing memory-driven industry thematic problem
rewriting, 2, performing
hybrid intention recognition and tool calling routing, 3, performing dynamic skill graph arrangement based on graph calculation: constructing a water conservancy field skill graph by utilizing a graph calculation technology, representing skill nodes and subtasks as a
directed acyclic graph (DAG), and performing dynamic skill graph arrangement based on graph calculation. The method comprises the following steps of: 1, selecting an intention recognition result, matching skill nodes and subtasks according to task requirements in combination with the routing strategy and the intention recognition result to dynamically generate an
execution plan, 4, carrying out parameter self-diagnosis and multi-round clarification, and 5, carrying out ReAct closed-loop feedback and field iteration: adopting a ReAct normal form to combine model reasoning and actions to form multi-round closed-loop interaction, and carrying out field iteration on the multi-round closed-loop interaction. And adjusting a reasoning path according to feedback in each round of iteration, introducing an early stop mechanism, and terminating iteration in advance when a model
execution plan generation result accords with expectation.