The application relates to the technical field of
automation operation and maintenance, and discloses an intention recognition method and
system based on dynamic ontology evolution and multi-agent, which comprises the following steps: receiving a
natural language instruction, performing entity extraction and probabilistic linking by using a dynamic ontology
knowledge base, and generating an initial intention based on predicate analysis; automatically completing missing key slots by using a
probabilistic graph model, and generating a standardized intention; decomposing the standardized intention into an atomic subtask sequence, dynamically matching an execution agent based on an agent capability-demand matrix, generating a collaborative
workflow, controlling the execution agent to call an atomic tool to execute a task, performing causal
correlation analysis on multi-source results according to
logical relations between ontology instances, generating a structured reasoning chain, and feeding back; and extracting a new treatment script based on execution feedback by using an evolution engine, and updating an ontology
knowledge base and an agent confidence degree. The application can realize accurate understanding, automatic execution and
adaptive evolution of a
knowledge base of a fuzzy operation and maintenance intention.