Real-time black-box optimization for dynamic discrete environments using embedded Ising machines
Tomoya Kashimata, Yohei Hamakawa, Masaya Yamasaki, Kosuke Tatsumura · 2026
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Description
Four researchers, Tomoya Kashimata, Yohei Hamakawa, Masaya Yamasaki, and Kosuke Tatsumura, present a 2026 method for picking the best action in systems that must decide fast while conditions keep changing. Many real systems must choose among huge numbers of combined options. Standard trial and error methods cannot search that space well. The best choice keeps shifting over time.
Their method extends an approach built on an Ising machine, a device that searches for good combinations with care for how choices affect each other. The machine explores options while tracking changes in the setting, with the goal of raising the average reward over many trials. The team tests the idea on a wireless system with moving users and reports that the method adapts well as users move.
Catalog record
| CREATOR | Tomoya Kashimata, Yohei Hamakawa, Masaya Yamasaki, Kosuke Tatsumura |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 58 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |