The invention discloses an agent decision-making model based on memory-learning
collaboration and application thereof, and the method comprises the steps: S1, constructing an agent feature attribute module which comprises the static attribute feature and the dynamic attribute feature of each agent; s2, constructing an
intelligent agent behavior set module which is used for selecting
intelligent agent individual behaviors and organizing behaviors, and S3, constructing an
intelligent agent behavior mode module which combines the state of the intelligent
agent behavior mode module with perceived information and refers to an accumulated memory set of the intelligent
agent behavior mode module, generating an
action plan of the next step under the guidance of the
behavior rule according to the following formula, so as to update the own state; step S4, constructing an interaction mechanism between intelligent agents, wherein the interaction mechanism comprises a memory mechanism formed by an individual memory
library, a
group memory library and a memory buffer
pool; interaction between the intelligent agent and the environment and between the intelligent agent and other intelligent agents is established, and the intelligent agent continuously updates a learning mechanism of a
decision strategy in continuous learning; a memory and learning collaborative decision-making mechanism with double functions of history and experience is introduced in the decision-making process of the intelligent agent; a cyclic feedback mechanism between decision memory and learning of the agent is established, a memory credibility evaluation mechanism is provided, the memory credibility is dynamically evaluated, self-adaptive updating of the memory is realized, and effective support is provided in the
decision process, so that the modeling quality of the individual Agent is improved.