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1. Real-Time LaCAM for Real-Time MAPF

   https://doi.org/10.1609/socs.v18i1.35993  

   Liang, Runzhe; Veerapaneni, Rishi; Harabor, Daniel; Li, Jiaoyang; Likhachev, Maxim (July 2025, Proceedings of the International Symposium on Combinatorial Search)

   The vast majority of Multi-Agent Path Finding (MAPF) methods with completeness guarantees require planning full-horizon paths. However, planning full-horizon paths can take too long and be impractical in real-world applications. Instead, real-time planning and execution, which only allows the planner a finite amount of time before executing and replanning, is more practical for real-world multi-agent systems. Several methods utilize real-time planning schemes but none are provably complete, which leads to livelock or deadlock. Our main contribution is Real-Time LaCAM, the first Real-Time MAPF method with provable completeness guarantees. We do this by leveraging LaCAM in an incremental fashion. Our results show how we can iteratively plan for congested environments with a cutoff time of milliseconds while still maintaining the same success rate as full-horizon LaCAM. We also show how it can be used with a single-step learned MAPF policy. 

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2. Real-data-driven real-time reconfigurable microwave reflective surface

   https://doi.org/10.1038/s41467-023-43473-y  

   Wen, Erda; Yang, Xiaozhen; Sievenpiper, Daniel F. (November 2023, Nature Communications)

   Abstract Manipulating the electromagnetic (EM) scattering behavior from an arbitrary surface dynamically on arbitrary design goals is an ultimate ambition for many EM stealth and communication problems, yet it is nearly impossible to accomplish with conventional analysis and optimization techniques. Here we present a reconfigurable conformal metasurface prototype as well as a workflow that enables it to respond to multiple design targets on the reflection pattern with extremely low on-site computing power and time. The metasurface is driven by a sequential tandem neural network which is pre-trained using actual experimental data, avoiding any possible errors that may arise from calculation, simulation, or manufacturing tolerances. This platform empowers the surface to operate accurately in a complex environment including varying incident angle and operating frequency, or even with other scatterers present close to the surface. The proposed data-driven approach requires minimum amount of prior knowledge and human effort yet provides maximized versatility on the reflection control, stepping towards the end form of intelligent tunable EM surfaces. 

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3. Real monodromy action

   https://doi.org/10.1016/j.amc.2019.124983  

   Hauenstein, Jonathan D.; Regan, Margaret H. (May 2020, Applied Mathematics and Computation)
4. Edge Distribution of Thinned Real Eigenvalues in the Real Ginibre Ensemble

   https://doi.org/10.1007/s00023-022-01182-0  

   Baik, Jinho; Bothner, Thomas (April 2022, Annales Henri Poincaré)

   Abstract This paper is concerned with the explicit computation of the limiting distribution function of the largest real eigenvalue in the real Ginibre ensemble when each real eigenvalue has been removed independently with constant likelihood. We show that the recently discovered integrable structures in [2] generalize from the real Ginibre ensemble to its thinned equivalent. Concretely, we express the aforementioned limiting distribution function as a convex combination of two simple Fredholm determinants and connect the same function to the inverse scattering theory of the Zakharov–Shabat system. As corollaries, we provide a Zakharov–Shabat evaluation of the ensemble’s real eigenvalue generating function and obtain precise control over the limiting distribution function’s tails. The latter part includes the explicit computation of the usually difficult constant factors. 

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5. Real-time MLton: A Standard ML runtime for real-time functional programs

   https://doi.org/10.1017/S0956796821000174  

   SHIVKUMAR, BHARGAV; MURPHY, JEFFREY; ZIAREK, LUKASZ (January 2021, Journal of Functional Programming)

   Abstract There is a growing interest in leveraging functional programming languages in real-time and embedded contexts. Functional languages are appealing as many are strictly typed, amenable to formal methods, have limited mutation, and have simple but powerful concurrency control mechanisms. Although there have been many recent proposals for specialized domain-specific languages for embedded and real-time systems, there has been relatively little progress on adapting more general purpose functional languages for programming embedded and real-time systems. In this paper, we present our current work on leveraging Standard ML (SML) in the embedded and real-time domains. Specifically, we detail our experiences in modifying MLton, a whole-program optimizing compiler for SML, for use in such contexts. We focus primarily on the language runtime, reworking the threading subsystem, object model, and garbage collector. We provide preliminary results over a radar-based aircraft collision detector ported to SML. 

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