Bilevel method and system for designing multi-agent systems and simulators
US-2022129695-A1 · Apr 28, 2022 · US
Intelligent recommendation method and apparatus, model training method and apparatus, electronic device, and storage medium
US12585716B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12585716-B2 |
| Application number | US-202117445905-A |
| Country | US |
| Kind code | B2 |
| Filing date | Aug 25, 2021 |
| Priority date | Dec 25, 2020 |
| Publication date | Mar 24, 2026 |
| Grant date | Mar 24, 2026 |
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- Title
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Abstract
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Provided are an intelligent recommendation method and apparatus, a model training method and apparatus, an electronic device, and a storage medium, which relate to artificial intelligence technologies, and are applicable to the intelligent recommendation and the intelligent transportation technologies. The intelligent recommendation method includes: determining an object recommendation request; determining, according to a multi-agent strategy model and the object recommendation request, object execution actions of at least two agent objects matching the object recommendation request; determining a target object execution action according to the object execution actions; and recommending the object recommendation request to a target agent object corresponding to the target object execution action.
First claim
Opening claim text (preview).
What is claimed is: 1 . An intelligent recommendation method, executed by an electronic device and comprising: determining an object recommendation request, wherein the object recommendation request is a charging station recommendation request; determining, according to a multi-agent strategy model and the object recommendation request, object execution actions of at least two agent objects matching the object recommendation request, wherein the at least two agent objects are charging stations; determining a target object execution action according to the object execution actions; and recommending the object recommendation request to a target agent object corresponding to the target object execution action; wherein the multi-agent strategy model is trained according to a value target function of the multi-agent strategy model and a strategy target function of the multi-agent strategy model; wherein the strategy target function of the multi-agent strategy model is determined based on the following equations: L A ( θ a ) = - E t ′ [ min ( ρ t ′ i A ˆ t ′ i , clip ( ρ t ′ i , 1 - ϵ , 1 + ϵ ) A ˆ t ′ i ) ] p t ′ i = π θ a ( a t ′ i | o t ′ i ) π θ t ′ a ( a t ′ i | o t ′ i ) A ^ t ′ i = R t ′ : t + Y ( T t - T t ′ ) V
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based on feedback of a supervisor · CPC title
by evaluating different subsets according to an optimisation criterion, e.g. class separability, forward selection or backward elimination · CPC title
Selection of pattern recognition techniques, e.g. of classifiers in a multi-classifier system · CPC title
Machine learning · CPC title
Reinforcement learning · CPC title
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- What does patent US12585716B2 cover?
- Provided are an intelligent recommendation method and apparatus, a model training method and apparatus, an electronic device, and a storage medium, which relate to artificial intelligence technologies, and are applicable to the intelligent recommendation and the intelligent transportation technologies. The intelligent recommendation method includes: determining an object recommendation request;…
- Who is the assignee on this patent?
- Beijing Baidu Netcom Sci & Tech Co Ltd
- What technology area does this patent fall under?
- Primary CPC classification G06F16/9535. Mapped technology areas include Physics.
- When was this patent published?
- Publication date Tue Mar 24 2026 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
- What related patents are in patentsdb?
- We list 4 related publications on this page (citations in our corpus or others sharing the same primary CPC).