Autonomous learning method and system of agent for man-machine cooperative work

A technology of autonomous learning and human-machine collaboration, applied in the field of autonomous learning methods and systems of agents, can solve the problems of inability to adapt and high demonstration costs, and achieve the effect of efficient utilization and reduction of demonstration costs

Active Publication Date: 2019-06-07
启元世界(北京)信息技术服务有限公司
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AI Technical Summary

Problems solved by technology

The expert system will constantly update and summarize the knowledge and experience of experts, and form a knowledge base in combination with rule programming, but it cannot adapt to the dynamic changes in the complex environment. In addition, it learns and trains the model through the guidance of experts. The demonstration cost of experts is high, and only It can represent the level of experts and cannot adapt to the dynamic changes of participants

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  • Autonomous learning method and system of agent for man-machine cooperative work
  • Autonomous learning method and system of agent for man-machine cooperative work

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Embodiment Construction

[0018] In order to make the object, technical solution and advantages of the present invention clearer, the implementation manner of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0019] Some technical terms involved in the embodiments of the present invention are explained below.

[0020] Both environment and action are technical terms involved in Reinforcement Learning (RL). The environment refers to the scene where the agent performs actions, interacts with the agent, and sends the current state of the environment to the agent. Actions are actions performed by an agent in response to the current state of the environment. Reinforcement learning, also known as reinforcement learning, refers to a class of problems that are continuously learned from interacting with the environment and methods for solving such problems. The problem of reinforcement learning can be described as an agent learning from the interac...

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Abstract

The invention belongs to the technical field of artificial intelligence. The invention discloses an autonomous learning method and system of an agent for man-machine cooperative work. The method comprises the steps of obtaining a cooperation data set, training a cooperation agent and a simulation agent according to the cooperation data set; and assessing whether the cooperation agent and the simulation agent meet assessment requirements or not according to the obtained assessment data generated by cooperation of the trained cooperation agent and the simulation agent in the environment, judgingwhether the trained simulation agent needs new imitation learning or not if the assessment requirements are met, and ending autonomous learning of the trained cooperation agent if the assessment requirements are not met. The system comprises a cooperation agent, a simulation agent and a server. Through the scheme, the dynamic change of the environment can be adapted, the same performance effect can be obtained in the similar environment, the demonstration behaviors of different teaches can be simulated, so that the trained intelligent agent can adapt to the dynamic change of the teaches, andthe teaches with different operation levels can also achieve the same cooperation effect.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence, and in particular relates to an autonomous learning method and system for an intelligent body oriented to man-machine collaborative work. Background technique [0002] In the human-machine collaboration mode, the agent (the entity can be a robot) cooperates with humans to complete corresponding tasks, so the agent needs to have the ability to cooperate with humans. [0003] In the prior art, the agent can have this ability through an expert system. The expert system uses the knowledge and problem-solving methods of human experts to deal with problems in this field through a large number of expert-level knowledge and experience in the field. The expert system will constantly update and summarize the knowledge and experience of experts, and form a knowledge base in combination with rule programming, but it cannot adapt to the dynamic changes in the complex environment. In addition, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/66G06N3/04G06N3/08
Inventor 孟红唐振坤
Owner 启元世界(北京)信息技术服务有限公司
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