SMIX(λ\lambda): Enhancing Centralized Value Functions for Cooperative Multi-Agent Reinforcement Learning

Learning a stable and generalizable centralized value function (CVF) is a crucial but challenging task in multi-agent reinforcement learning (MARL), as it has to deal with the issue that the joint action space increases exponentially with the number of agents in such scenarios. This paper proposes an approach, named SMIX(${\lambda}$), to address the issue using an efficient off-policy centralized training method within a flexible learner search space. As importance sampling for such off-policy training is both computationally costly and numerically unstable, we proposed to use the ${\lambda}$-return as a proxy to compute the TD error. With this new loss function objective, we adopt a modified QMIX network structure as the base to train our model. By further connecting it with the ${Q(\lambda)}$ approach from an unified expectation correction viewpoint, we show that the proposed SMIX(${\lambda}$) is equivalent to ${Q(\lambda)}$ and hence shares its convergence properties, while without being suffered from the aforementioned curse of dimensionality problem inherent in MARL. Experiments on the StarCraft Multi-Agent Challenge (SMAC) benchmark demonstrate that our approach not only outperforms several state-of-the-art MARL methods by a large margin, but also can be used as a general tool to improve the overall performance of other CTDE-type algorithms by enhancing their CVFs

Structural and Functional Alterations in Visual Pathway After Optic Neuritis in MOG Antibody Disease: A Comparative Study With AQP4 Seropositive NMOSD

Background: Optic neuritis (ON) is an important clinical manifestation of neuromyelitis optic spectrum disease (NMOSD). Myelin oligodendrocyte glycoprotein (MOG) antibody-related and aquaporin 4 (AQP4) antibody-related ON show different disease patterns. The aim of this study was to explore the differences in structure and function of the visual pathway in patients with ON associated with MOG and AQP4 antibodies.Methods: In this prospective study, we recruited 52 subjects at Beijing Tiantan Hospital, including 11 with MOG Ig+ ON (MOG-ON), 13 with AQP4 Ig+ ON (AQP4-ON), and 28 healthy controls (HCs). Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) of optic radiation (OR), primary visual cortex volume (V1), brain volume, and visual acuity (VA) were compared among groups. A multiple linear regression was used to explore associations between VA and predicted factors. In addition, we used optical coherence tomography (OCT) to examine thickness of the peripapillary retinal nerve fiber layer (pRNFL) and retinal ganglion cell complex (GCC) in a separate cohort consisting of 15 patients with ON (8 MOG-ON and 7 AQP4-ON) and 28 HCs.Results: Diffusion tensor imaging showed that the FA of OR was lower than controls in patients with AQP4-ON (p = 0.001) but not those with MOG-ON (p = 0.329) and was significantly different between the latter two groups (p = 0.005), while V1 was similar in patients with MOG-ON and AQP4-ON (p = 0.122), but was lower than controls in AQP4-ON (p = 0.002) but not those with MOG-ON (p = 0.210). The VA outcomes were better in MOG-ON than AQP4-ON, and linear regression analysis revealed that VA in MOG-ON and AQP4-ON was both predicted by the FA of OR (standard β = −0.467 and −0.521, p = 0.036 and 0.034). Both patients of MOG-ON and AQP4-ON showed neuroaxonal damage in the form of pRNFL and GCC thinning but showed no statistically significant difference (p = 0.556, 0.817).Conclusion: The structural integrity of OR in patients with MOG-ON, which is different from the imaging manifestations of AQP4-ON, may be a reason for the better visual outcomes of patients with MOG-ON

A multicentre, prospective, double-blind study comparing the accuracy of autoantibody diagnostic assays in myasthenia gravis: the SCREAM studyResearch in context

Summary: Background: Laboratory determination of autoantibodies against acetylcholine receptor (AChR), muscle-specific kinase (MuSK) and other autoantigens have been integrated into the diagnosis of myasthenia gravis (MG). However, evidence supporting the selection of methodologies is lacking. Methods: In this prospective, multicentre cohort study, we recruited patients with suspected MG to evaluate the diagnostic accuracy of cell-based assay (CBA), radioimmunoprecipitation assay (RIPA) and enzyme-linked immunosorbent assay (ELISA) in detecting AChR and MuSK autoantibodies. This study is registered with www.clinicaltrials.gov, number NCT05219097. Findings: 2272 eligible participants were recruited, including 2043 MG, 229 non-MG subjects. AChR antibodies were detected in 1478, 1310, and 1280 out of a total of 2043 MG patients by CBA, RIPA, and ELISA, respectively; sensitivity, 72.3% (95% CI, 70.3–74.3), 64.1% (95% CI, 62.0–66.2), 62.7% (95% CI, 60.5–64.8); specificity, 97.8% (95% CI, 95.0–99.3), 97.8% (95% CI, 95.0–99.3), 94.8% (95% CI, 91.9–97.7). MuSK antibodies were found in 59, 50, and 54 from 2043 MG patients by CBA, RIPA and ELISA, respectively; sensitivity, 2.9% (95% CI, 2.2–3.7), 2.4% (95% CI, 1.8–3.2), 2.6% (95% CI, 2.0–3.4); specificity, 100% (95% CI, 98.4–100), 100% (95% CI, 98.4–100), and 99.1% (95% CI, 96.9–99.9). The area under the curve of AChR antibodies tested by CBA was 0.858, and there were statistical differences with RIPA (0.843; p = 0.03) and ELISA (0.809; p < 0.0001). Interpretation: CBA has a higher diagnostic accuracy compared to RIPA or ELISA in detecting AChR and MuSK autoantibodies for MG diagnosis. Funding: New Terrain Biotechnology, Inc., Tianjin, China