Reinforcement Learning Patents: Top Companies & Filing Trends 2026
Reinforcement Learning Patents: Who Files, Where the Claim Space Sits
Filings grew 61% from 2021 to 2024, rising from 2,294 to 3,700 records a year before the peak, with 2025-26 counts still filling in as publications lag filing. Annual filings rose from 486 in 2017 to a peak of 3,700 in 2024, including a 61% increase between 2021 (2,294) and 2024 (3,700). 2025 and 2026 counts are still partial because of publication lag and should not be read as a decline.
- 1LG ELECTRONICS INC7.9%
- 2SAMSUNG ELECTRONICS CO LTD4.7%
- 3INTEL CORP3.7%
- 4GOOGLE LLC2.6%
- 5MICROSOFT TECHNOLOGY LICENSING LLC1.5%
See the full reinforcement learning patent landscape analysis in Eureka
- The complete ranking, not just the top five
- Every IPC branch with its share of the corpus
- The most-cited records, and where claim space is still thin
Common questions about the reinforcement learning patent landscape
Who are the leading patent holders in reinforcement learning?
The assignee ranking covers 100 companies measured by patent family/record counts, led by a single filer with 3,068 records, well ahead of a fifth-place holder at 594 and a tenth-place holder at 451. The top 10 combined account for 27.2% of the 38,627 records in scope, which means the remaining assignees in the ranking, plus a large population outside it, hold the majority of filings as a long tail. Large diversified electronics and software companies dominate the upper ranks, reflecting reinforcement learning’s role as a component technology inside broader AI and systems patents rather than a standalone niche.
Is reinforcement learning patent filing still growing?
Yes, through the last complete filing year in this dataset. Filings rose from 2,294 in 2021 to 3,700 in 2024, a 61% increase over that span, and 2024 is the most recent year that can be treated as a full year of data. 2025 and 2026 counts appear lower only because publication typically lags actual filing by about 18 months, so those years are still filling in rather than reflecting a genuine slowdown.
What technology areas overlap most with reinforcement learning patents?
Core AI computing methods (IPC class G06N) appear in 21.6% of the 38,627 records in scope, and general electric digital data processing (G06F) appears in 16.4%. Beyond that core, image and video processing, wireless communication networks, business data processing and healthcare informatics each carry between roughly 4.5% and 6.1% of records, showing reinforcement learning claims extending well beyond pure algorithm patents into applied domains. Because a single record can carry multiple IPC classes, these shares add up to more than 100% and should not be summed.
Disclaimer. This analysis is based on Patsnap Eureka data drawn from a limited snapshot of global patent records and is provided for general information and reference only. Patent data carries inherent limitations — recent filings are under-counted because of publication lag, counts may be on a record or family basis, classification and applicant-name data may contain errors or duplicates, and the underlying search query defines the scope shown — so the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing here is an exhaustive prior-art, novelty, freedom-to-operate or validity search, nor does it constitute legal, financial or professional advice, and it should not be relied upon as such. Verify independently and review with qualified patent and legal professionals before acting on it.
Method: Filing trend and technology composition. Derived from a Patsnap search on Reinforcement Learning Patent Landscape covering 2015–2026, data cut-off 2026-08-31. Counts reflect published records only and shift as new filings publish. Every share divides by all records in scope. Data: Patsnap Eureka. See the full landscape report.