4results about How to "Solve decision problems" patented technology

This invention discloses a D2D user resource allocation method and storage medium based on a deep reinforcement learning algorithm, relating to the field of wireless communication technology. The method includes: constructing a wireless network model and discretizing the D2D transmit power; constructing a user signal-to-noise ratio calculation model with maximizing the communication system throughput as the optimization objective; setting a prediction policy network π, a prediction value network Q, a target policy network π′, and a target value network Q'; modeling the D2D communication environment as a Markov decision process, treating the D2D transmitter as an agent, iteratively loading the parameters of the target policy network to generate a policy that interacts with the environment, determining the state space, action space, and reward function; using the MAAC algorithm to optimize the policy for each D2D user; using a soft update method to iteratively update the parameters of the target policy network and the target value network until training is complete; and having the D2D user download the trained parameters of the target policy network and improve their policy.

The application provides a large model multi-agent A2A virtual power grid dispatching and power selling system and method, which comprises a vertical field energy large model module, an MCP tool layer module, an A2A multi-agent negotiation layer module and an application service layer module; the vertical field energy large model module serves as a system core reasoning engine; the large model multi-agent A2A virtual power grid dispatching and power selling system and method; the large model multi-agent A2A virtual power grid dispatching and power selling system provided by the application improves system operation safety and reliability, constructs a continuous learning closed loop of execution, evaluation, optimization and updating, iteratively optimizes dispatching and power selling strategies through review and optimization of agents, strengthens system adaptive and autonomous evolution capabilities, guarantees long-term stable and efficient operation, and provides a new technical path for intelligent operation of a virtual power grid.

An embodiment of the present disclosure provides a method for providing digital production planning information, comprising: providing an extensible software model and a logic set for generating production planning data to a client; receiving first input data comprising benchmark information of a manufacturing production system and second input data for parameter setting; and based on the first input data and the second input data, performing at least one of learning, evaluation, operation, deployment and management on at least one strategy to provide production planning data to the client.

The embodiment of the application provides a kind of lane boundary determination method, device, vehicle, medium and program product, which obtains the multi-source lane boundary data collected by vehicle, and the multi-source lane boundary data is the data obtained by identifying lane boundary based on multiple sensors;According to the multi-source lane boundary data, at least one lane boundary data set of the same position is determined, each lane boundary data set includes at least one candidate lane boundary data;For each lane boundary data set, according to the preset lane boundary rule library, the lane boundary data set is corrected to obtain the target lane boundary data applied to control vehicle, and the lane boundary rule library is constructed based on the marking feature of standard lane boundary, the spatial topology feature of standard lane boundary, the lane boundary combination feature of standard lane boundary and priority feature.The technical scheme can more accurately realize the identification of lane boundary information.