5 results about "Alternative strategy" patented technology

A method includes determining, based on historical access data and a current data parameter, a root node representing a current state and at least one child node including an alternative strategy. The method further includes generating at least one extension node including an alternative strategy based on predictions of the historical access data and the at least one child node. The method further includes generating a first state vector by encoding tree-structured data including the root node, the child node, and the extension node. The method further includes selecting the alternative strategy corresponding to the child node or the extension node based on the first state vector to generate the retention strategy. Through this method, predicted future states can be integrated in a process of generating the retention strategy, which provides a more comprehensive perspective for decision-making, thereby improving the accuracy and effectiveness of the strategy.

The present disclosure relates to a method, an apparatus and a computer program product for generating a retention policy. The method includes determining a root node representing a current state and at least one child node including an alternative policy based on historical access data and a current data parameter. The method further includes generating at least one extension node including an alternative policy based on the prediction of the historical access data and the at least one child node. The method further includes generating a first state vector by encoding tree structure data including root nodes, child nodes, and extension nodes. And selecting an alternative strategy corresponding to the child node or the extension node based on the first state vector so as to generate a reservation strategy. Through the mode, the predicted future state can be integrated in the process of generating the retention strategy, and a more comprehensive view angle is provided for decision making, so that the accuracy and effectiveness of the strategy are improved.

The application discloses a kind of security automatic driving methods based on double alternative diffusion strategy, for the problem that traditional off-line reinforcement learning may cause unsafe behavior in automatic driving task due to extrapolation error, propose to use two diffusion models as mutually alternative strategy, and use integrated network containing multiple action value networks as policy evaluation network;By training two diffusion models and integrated network in offline environment, the uncertainty of the actions generated by the two strategies is evaluated using the integrated network during the deployment phase, and the strategy with lower uncertainty is selected as the final driving strategy, thereby ensuring the safety of the automatic driving task during the deployment phase.

This invention relates to a method for selecting a coordinated operation strategy for urban rail transit and urban rail transit trains, comprising: constructing a set of alternative operation strategies for urban rail transit and urban rail transit trains from the perspectives of routes, stops, and train formations; determining feasible strategies suitable for urban rail transit and urban rail transit trains based on the set of alternative strategies; and establishing a coordinated optimization model for the operation schemes of urban rail transit and urban rail transit trains based on the feasible strategies, and solving for the route departure frequency, stop scheme, and train formation number under each feasible strategy. This invention provides a clear answer to "which operation organization level strategy to adopt" in specific situations of multi-mode rail transit, thereby making up for the lack of a set of operation organization level strategy selection methods for urban rail transit and urban rail transit to cope with variable passenger flows.

The present invention discloses a resource-cost-based strategy selection method, system, electronic device, and storage medium. The method comprises the following steps: S1, calculating the memory required for each alternative strategy and the minimum CPU speed required for it to run within a specified time; S2, calculating the functional realization degree of each alternative strategy; S3, selecting an effective strategy from the alternative strategy using a multi-objective optimization algorithm based on the memory occupied, the minimum CPU speed required, and the functional realization degree of the alternative strategy; S4, screening the effective strategy according to set memory, CPU speed, and functional realization degree thresholds to obtain a preferred strategy. The present invention evaluates hardware resource cost by calculating the memory occupied and the minimum CPU speed requirement of the strategy and setting corresponding thresholds, while also evaluating the functional realization degree, so as to select a preferred strategy that reasonably balances the functional realization degree and resource cost.