Tootfinder

Marx's Theory of Value at the Frontiers Classical Political Economics, Imperialism and Ecological Breakdown
By Güney Işıkara, Patrick Mokre
I'd be interested in reading this, but £116 for 200 pages?
The piss is being taken, along with the money.
Marx's Theory of Value at the Frontiers: Classical Political Economics

Marx's Theory of Value at the Frontiers: Classical Political Economics, Imperialism and Ecological Breakdown
Why do humans produce the things they do, in the way they do it?  As this book shows, the classical political economics approach to value and prices has fundamental implications for analyzing the historical trajectory of capitalism. It demonstrates that the classical political economists’ approach to value and prices, which finds its most advanced formulation in Marx, sheds light on the source of profits, exploitation, whether equivalents are exchanged in trade, dynamics of asymmetric and

A Solution to the Hierarchy Problem with Non-Linear Quantum Mechanics
David E. Kaplan, Surjeet Rajendran
https://arxiv.org/abs/2510.12030 https://arxiv.org…

A Solution to the Hierarchy Problem with Non-Linear Quantum Mechanics
We argue that the hierarchy problem of the standard model of particle physics can be solved by adding a state-dependent term to the Higgs sector. We present an example of a scalar field with a Higgs-like potential with an additional term proportional to the expectation value of the squared Higgs field operator. We show that the mass can be parametrically lighter than the theory's energy-momentum cutoff without fine tuning. We find the Higgs mass can be technically natural, even with a Planck-sc…

Function spaces and trace theorems for maximally subelliptic boundary value problems
Brian Street
https://arxiv.org/abs/2510.12775 https://arxiv.org/pdf/25…

Function spaces and trace theorems for maximally subelliptic boundary value problems
We introduce Besov and Triebel--Lizorkin spaces on a manifold with boundary adapted to Hörmander vector fields, near a so-called non-characteristic point of the boundary. We prove sharp results in these spaces for the corresponding restriction and trace operators, show these operators are retractions, and other related results. This is the second paper in a forthcoming series devoted to a general theory of maximally subelliptic boundary value problems, and lays the function space foundation fo…

S-D-RSM: Stochastic Distributed Regularized Splitting Method for Large-Scale Convex Optimization Problems
Maoran Wang, Xingju Cai, Yongxin Chen
https://arxiv.org/abs/2511.10133 https://arxiv.org/pdf/2511.10133 https://arxiv.org/html/2511.10133
arXiv:2511.10133v1 Announce Type: new
Abstract: This paper investigates the problems large-scale distributed composite convex optimization, with motivations from a broad range of applications, including multi-agent systems, federated learning, smart grids, wireless sensor networks, compressed sensing, and so on. Stochastic gradient descent (SGD) and its variants are commonly employed to solve such problems. However, existing algorithms often rely on vanishing step sizes, strong convexity assumptions, or entail substantial computational overhead to ensure convergence or obtain favorable complexity. To bridge the gap between theory and practice, we integrate consensus optimization and operator splitting techniques (see Problem Reformulation) to develop a novel stochastic splitting algorithm, termed the \emph{stochastic distributed regularized splitting method} (S-D-RSM). In practice, S-D-RSM performs parallel updates of proximal mappings and gradient information for only a randomly selected subset of agents at each iteration. By introducing regularization terms, it effectively mitigates consensus discrepancies among distributed nodes. In contrast to conventional stochastic methods, our theoretical analysis establishes that S-D-RSM achieves global convergence without requiring diminishing step sizes or strong convexity assumptions. Furthermore, it achieves an iteration complexity of $\mathcal{O}(1/\epsilon)$ with respect to both the objective function value and the consensus error. Numerical experiments show that S-D-RSM achieves up to 2--3$\times$ speedup compared to state-of-the-art baselines, while maintaining comparable or better accuracy. These results not only validate the algorithm's theoretical guarantees but also demonstrate its effectiveness in practical tasks such as compressed sensing and empirical risk minimization.
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Viscosity CBFs: Bridging the Control Barrier Function and Hamilton-Jacobi Reachability Frameworks in Safe Control Theory
Dylan Hirsch, Jaime Fern\'andez Fisac, Sylvia Herbert
https://arxiv.org/abs/2510.09929

Viscosity CBFs: Bridging the Control Barrier Function and Hamilton-Jacobi Reachability Frameworks in Safe Control Theory
Control barrier functions (CBFs) and Hamilton-Jacobi reachability (HJR) are central frameworks in safe control. Traditionally, these frameworks have been viewed as distinct, with the former focusing on optimally safe controller design and the latter providing sufficient conditions for safety. A previous work introduced the notion of a control barrier value function (CB-VF), which is defined similarly to the other value functions studied in HJR but has certain CBF-like properties. In this work, …

Latent Class Logit Kernel Framework for Surrogate Safety: Identifying Behavioural Thresholds through Conflict Indicator Profiles
Rulla Al-Haideri, Changhe Liu, Karim Ismail, Bilal Farooq, Chi Zhang
https://arxiv.org/abs/2510.12012

Latent Class Logit Kernel Framework for Surrogate Safety: Identifying Behavioural Thresholds through Conflict Indicator Profiles
Crash data objectively characterize road safety but are rare and often unsuitable for proactive safety management. Traffic conflict indicators such as time-to-collision (TTC) provide continuous measures of collision proximity but require thresholds to distinguish routine from safety-critical interactions. Extreme Value Theory (EVT) offers statistically defined thresholds, yet these do not necessarily represent how drivers perceive and respond to conflict. This study introduces a behavioural mod…

Multi-objective Bayesian optimization for blocking in extreme value analysis and its application in additive manufacturing
Shehzaib Irfan, Nabeel Ahmad, Alexander Vinel, Daniel F. Silva, Shuai Shao, Nima Shamsaei, Jia Liu
https://arxiv.org/abs/2510.11960

Multi-objective Bayesian optimization for blocking in extreme value analysis and its application in additive manufacturing
Extreme value theory (EVT) is well suited to model extreme events, such as floods, heatwaves, or mechanical failures, which is required for reliability assessment of systems across multiple domains for risk management and loss prevention. The block maxima (BM) method, a particular approach within EVT, starts by dividing the historical observations into blocks. Then the sample of the maxima for each block can be shown, under some assumptions, to converge to a known class of distributions, which …

On extremes for Gaussian subordination
Shuyang Bai, Marie-Christine D\"uker
https://arxiv.org/abs/2510.10578 https://arxiv.org/pdf/2510.10578

On extremes for Gaussian subordination
This paper investigates extreme value theory for processes obtained by applying transformations to stationary Gaussian processes, also called subordinated Gaussian processes. The main contributions are as follows. First, we refine the method of \cite{sly2008nonstandard} to allow the covariance of the underlying Gaussian process to decay more slowly than any polynomial rate, nearly matching Berman's condition. Second, we extend the theory to a multivariate setting, where both the subordinated pr…

Anarcho-syndicalism is the belief that workers, as the fundamental producers of social value, must seize control of the means of production through direct action and autonomous organization. It rejects both capitalist private ownership and state-controlled systems, arguing instead for a decentralized federation of worker-managed industries. From my perspective, anarcho-syndicalism is not merely an economic strategy but a revolutionary theory of social transformation, one that places the work…

Gaussian Equivalence for Self-Attention: Asymptotic Spectral Analysis of Attention Matrix
Tomohiro Hayase, Beno\^it Collins, Ryo Karakida
https://arxiv.org/abs/2510.06685 https:…

Gaussian Equivalence for Self-Attention: Asymptotic Spectral Analysis of Attention Matrix
Self-attention layers have become fundamental building blocks of modern deep neural networks, yet their theoretical understanding remains limited, particularly from the perspective of random matrix theory. In this work, we provide a rigorous analysis of the singular value spectrum of the attention matrix and establish the first Gaussian equivalence result for attention. In a natural regime where the inverse temperature remains of constant order, we show that the singular value distribution of t…

Multi-Level Hybrid Monte Carlo / Deterministic Methods for Particle Transport Problems
Vincent N. Novellino, Dmitriy Y. Anistratov
https://arxiv.org/abs/2510.09545 https://

Multi-Level Hybrid Monte Carlo / Deterministic Methods for Particle Transport Problems
This paper presents multi-level hybrid transport (MLHT) methods for solving the neutral particle Boltzmann transport equation. The proposed MLHT methods are formulated on a sequence of spatial grids using a multi-level Monte Carlo (MLMC) approach. The general MLMC algorithm is defined by the recursive estimation of the expected value of a solution functional's correction with respect to a neighboring grid. MLMC theory optimizes the total computational cost for estimating a functional to within …

Quantized Dirac Fields in torsionful gravity: cosmological implications and links with the dark universe
Antonio Capolupo, Sante Carloni, Luca Fabbri, Simone Monda, Aniello Quaranta, Stefano Vignolo
https://arxiv.org/abs/2510.06874

Quantized Dirac Fields in torsionful gravity: cosmological implications and links with the dark universe
We consider a classical field in square torsion theory as a source of torsion for a quantum fermion field in FLRW metric. In the framework of QFT, we obtain vacuum contributions to the energy-momentum tensor and to the axial current that modify the dynamics of the classical field and the field equations as back-reaction. These contributions lead to a modified classical field and therefore to a modified torsion term $L^μ$ and expectation value of energy-momentum tensor $T^{μν}$ on the quantum…

Excitation energy of fission fragments within nuclear time-dependent density functional theory
Antonio Bjel\v{c}i\'c, Nicolas Schunck, Marc Verriere
https://arxiv.org/abs/2510.06701

Excitation energy of fission fragments within nuclear time-dependent density functional theory
The number and properties of the neutrons and photons emitted in nuclear fission are directly related to the excitation energy of the fission fragments when they are formed at scission. Though not observable experimentally because of the extremely short time scales, the excitation energy of fission fragments can be predicted by microscopic theory based on time-dependent density functional theory (TDDFT). Initial results on the value of the total kinetic energy of fission reactions were very pro…

Invariant Price of Anarchy: a Metric for Welfarist Traffic Control
Ilia Shilov, Mingjia He, Heinrich H. Nax, Emilio Frazzoli, Gioele Zardini, Saverio Bolognani
https://arxiv.org/abs/2512.05843 https://arxiv.org/pdf/2512.05843 https://arxiv.org/html/2512.05843
arXiv:2512.05843v1 Announce Type: new
Abstract: The Price of Anarchy (PoA) is a standard metric for quantifying inefficiency in socio-technical systems, widely used to guide policies like traffic tolling. Conventional PoA analysis relies on exact numerical costs. However, in many settings, costs represent agents' preferences and may be defined only up to possibly arbitrary scaling and shifting, representing informational and modeling ambiguities. We observe that while such transformations preserve equilibrium and optimal outcomes, they change the PoA value. To resolve this issue, we rely on results from Social Choice Theory and define the Invariant PoA. By connecting admissible transformations to degrees of comparability of agents' costs, we derive the specific social welfare functions which ensure that efficiency evaluations do not depend on arbitrary rescalings or translations of individual costs. Case studies on a toy example and the Zurich network demonstrate that identical tolling strategies can lead to substantially different efficiency estimates depending on the assumed comparability. Our framework thus demonstrates that explicit axiomatic foundations are necessary in order to define efficiency metrics and to appropriately guide policy in large-scale infrastructure design robustly and effectively.
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Value Alignment of Social Media Ranking Algorithms
Farnaz Jahanbakhsh, Dora Zhao, Tiziano Piccardi, Zachary Robertson, Ziv Epstein, Sanmi Koyejo, Michael S. Bernstein
https://arxiv.org/abs/2509.14434

Value Alignment of Social Media Ranking Algorithms
While social media feed rankings are primarily driven by engagement signals rather than any explicit value system, the resulting algorithmic feeds are not value-neutral: engagement may prioritize specific individualistic values. This paper presents an approach for social media feed value alignment. We adopt Schwartz's theory of Basic Human Values -- a broad set of human values that articulates complementary and opposing values forming the building blocks of many cultures -- and we implement an …

Data as Commodity: a Game-Theoretic Principle for Information Pricing
Pasquale Casaburi, Giovanni Piccioli, Pierpaolo Vivo
https://arxiv.org/abs/2510.07101 https://

Data as Commodity: a Game-Theoretic Principle for Information Pricing
Data is the central commodity of the digital economy. Unlike physical goods, it is non-rival, replicable at near-zero cost, and traded under heterogeneous licensing rules. These properties defy standard supply--demand theory and call for new pricing principles. We propose a game-theoretic approach in which the value of a data string emerges from strategic competition among N players betting on an underlying stochastic process, each holding partial information about past outcomes. A better-infor…

From negative to positive $\Lambda$ through cosmological decreasing temperatures and its connection to spacetime foliation and string theory
E. N. Nyergesy, I. G. M\'ari\'an, A. Trombettoni, I. N\'andori
https://arxiv.org/abs/2510.02244

From negative to positive $Λ$ through cosmological decreasing temperatures and its connection to spacetime foliation and string theory
String theories naturally predict a negative, while observations on the exponential expansion of the present Universe requires a positive value for the cosmological constant $Λ$. Solution to resolve this discrepancy is known in the framework of string theory and given for Asymptotically Safe (AS) quantum gravity by using Renormalization Group (RG). However, the former might describes unstable worlds and the latter lacks the inclusion of temperature which is otherwise crucial in the early Unive…

Spectral Bootstrap for Non-Parametric Simulation of Multivariate Extreme Events
Nisrine Madhar (UPCit\'e, LPSM), Juliette Legrand (LMBA, UBO), Maud Thomas (LPSM)
https://arxiv.org/abs/2509.26451

Spectral Bootstrap for Non-Parametric Simulation of Multivariate Extreme Events
Inference in extreme value theory relies on a limited number of extreme observations, making estimation challenging. To address this limitation, we propose a non-parametric bootstrap procedure, the multivariate extreme spectral bootstrap procedure, relying on the spectral representation of multivariate generalized Paretodistributed random vectors. Unlike standard bootstrap methods, our approach preserves the joint tail behaviour of the data and generates additional synthetic extreme data, there…

Gated X-TFC: Soft Domain Decomposition for Forward and Inverse Problems in Sharp-Gradient PDEs
Vikas Dwivedi, Enrico Schiassi, Monica Sigovan, Bruno Sixou
https://arxiv.org/abs/2510.01039

Gated X-TFC: Soft Domain Decomposition for Forward and Inverse Problems in Sharp-Gradient PDEs
Physics-informed neural networks (PINNs) and related methods struggle to resolve sharp gradients in singularly perturbed boundary value problems without resorting to some form of domain decomposition, which often introduce complex interface penalties. While the Extreme Theory of Functional Connections (X-TFC) avoids multi-objective optimization by employing exact boundary condition enforcement, it remains computationally inefficient for boundary layers and incompatible with decomposition. We pr…

Extreme Value Theory-enhanced Radio Maps for Handovers in Ultra-reliable Communications
Dian Echevarr\'ia P\'erez, Onel L. Alcaraz L\'opez, Hirley Alves
https://arxiv.org/abs/2509.22547

Extreme Value Theory-enhanced Radio Maps for Handovers in Ultra-reliable Communications
Efficient handover (HO) strategies are essential for maintaining the stringent performance requirements of ultra-reliable communication (URC) systems. This work introduces a novel HO framework designed from a physical-layer perspective, where the decision-making process focuses on determining the optimal time and location for performing HOs. Leveraging extreme value theory (EVT) and statistical radio maps, the proposed method predicts signal behaviour and enables efficient resource allocation. …

From a story in today’s Wall Street Journal about Woody Allen and his new novel:

Though he’s already at work on a second novel, he rarely reads fiction—“I feel like I’m wasting time.”
More often he reads philosophy and books by physicists.
“I keep thinking I’m going to learn something of deep value that’s going to make me feel better in life,” he says.
“It never does.”

Two Number Theory Items (and Woody Allen)
James Douglas Boyd has recently spent a lot of time interacting with Mochizuki and others at RIMS working in anabelian geometry. Material from interviews he conducted are available here (Mochizuki …

Impact IRR: Leveraging Modern Portfolio Theory to Define Impact Investments
Daniel Soliman
https://arxiv.org/abs/2509.22600 https://arxiv.org/pdf/2509.2260…

Impact IRR: Leveraging Modern Portfolio Theory to Define Impact Investments
The impact investment market has an estimated value of almost $1.6 trillion. Significant progress has been made in determining the financial returns of impact investing. Investors are still, however, in the early stages of determining impact return. In this study, the author proposes the use of impact internal rate of return (impact IRR) to evaluate and monitor impact investments. This approach, which utilizes components of modern portfolio theory, adapted financial tools, and existing datasets…

Partial sharing and cross sharing of entire function with its derivative
Sujoy Majumder, Nabadwip Sarkar, Debabrata Pramanik
https://arxiv.org/abs/2509.20273 https://

Partial sharing and cross sharing of entire function with its derivative
In the paper, we investigate the uniqueness problem of a power of an entire function that share one value partially with it's linear differential polynomial and obtain a result, which improves several previous results in a large scale. Also in the paper we include some applications of our main result. Moreover, we solve the question raised by Wang and Liu (Value cross-sharing of meromorphic functions, Comput. Methods Funct. Theory (2023). https://doi.org/10.1007/s40315-023-00481-9) for a specia…

RE: https://fediscience.org/@suomenantropologi/115614886106180185
Vale Keith Hart. That keynote from 2010 (link below) was (and still is) a compelling argument for reconnecting value theory to practical political economy by weaving together Marx's commodity fetishism, the concept of plural economy inspired by Mauss, and the digital revolution's radical cheapening of information.

Poincar\'e-Einstein 4-manifolds with conformally K\"ahler geometry
Mingyang Li, Hongyi Liu
https://arxiv.org/abs/2510.04928 https://arxiv.org/pdf/…

Poincaré-Einstein 4-manifolds with conformally Kähler geometry
We study 4-dimensional Poincaré-Einstein manifolds whose conformal class contains a Kähler metric. Such Einstein metrics are non-Kähler and admit a Killing field extending to the conformal infinity, and the Einstein equation reduces to a Toda-type equation. When the Killing field integrates to an $\mathbb{S}^1$-action, we formulate a Dirichlet boundary value problem and establish existence and uniqueness theory. This construction provides a non-perturbative realization of infinite-dimensiona…

Replaced article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- Egyptian Ratscrew: Discovering Dominant Strategies with Computational Game Theory
Justin Diamond, Ben Garcia
https://arxiv.org/abs/2304.01007
- Truthful and Almost Envy-Free Mechanism of Allocating Indivisible Goods: the Power of Randomness
Xiaolin Bu, Biaoshuai Tao
https://arxiv.org/abs/2407.13634 https://mastoxiv.page/@arXiv_csGT_bot/112811955506293858
- Learning the Value of Value Learning
Alex John London, Aydin Mohseni
https://arxiv.org/abs/2511.17714 https://mastoxiv.page/@arXiv_csAI_bot/115609411461995995
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On the propagation of mountain waves: linear theory
Adrian Constantin, J\"org Weber
https://arxiv.org/abs/2509.26125 https://arxiv.org/pdf/2509.26125

On the propagation of mountain waves: linear theory
We derive and establish a solution concept for the linear mountain wave problem in two dimensions. After linearizing the governing equations and a change of variables, the problem can be stated as a Dirichlet boundary value problem for a Helmholtz equation in terms of the vertical wind profile in the upper half-plane, with altitude-dependent potential (the Scorer parameter). To single out the correct solution, we have to make use of a radiation condition which is, due to the different physical …

Multivariate distributional modeling of low, moderate, and large intensities without threshold selection steps
Carlo Gaetan, Philippe Naveau
https://arxiv.org/abs/2510.02152 htt…

Multivariate distributional modeling of low, moderate, and large intensities without threshold selection steps
In fields such as hydrology and climatology, modelling the entire distribution of positive data is essential, as stakeholders require insights into the full range of values, from low to extreme. Traditional approaches often segment the distribution into separate regions, which introduces subjectivity and limits coherence. This is especially true when dealing with multivariate data. In line with multivariate extreme value theory, this paper presents a unified, threshold-free framework for mode…

Probability Density Estimation via Optimal Control
Markus Hegland, C. Yal\c{c}{\i}n Kaya
https://arxiv.org/abs/2510.00835 https://arxiv.org/pdf/2510.00835

Probability Density Estimation via Optimal Control
We employ optimal control theory to study the problem of estimating the probability density function from a data set originating from an unknown probability distribution. The original variational problem is reformulated as a multi-stage optimal control problem and the associated maximum principle, or conditions of optimality, is reduced to a two-point boundary-value problem with interior conditions. A numerical scheme is proposed to solve the discretization of this problem. Estimates of density…

Superluminal Liouville walls in 2d String Theory and space-like singularities
Sumit R. Das, Shaun D. Hampton, Sinong Liu
https://arxiv.org/abs/2509.12778 https://

Superluminal Liouville walls in 2d String Theory and space-like singularities
An interesting class of time dependent backgrounds in $1+1$ dimensional string theory involves worldsheet Liouville walls which move in (target space) time. When a parameter in such a background exceeds a certain critical value, the speed of the Liouville wall exceeds the speed of light, and there is no usual S-Matrix. We examine such backgrounds in the dual $c=1$ matrix model from the point of view of fluctuations of the collective field, and determine the nature of the emergent space-time per…

Thermodynamics of BTZ Black Holes in Bumblebee Gravity with Barrow Entropy with Cavity-Modification
H. Kaur, Prince A Ganai
https://arxiv.org/abs/2509.22129 https://

Thermodynamics of BTZ Black Holes in Bumblebee Gravity with Barrow Entropy with Cavity-Modification
We investigate the thermodynamics of $(2+1)$ dimensional BTZ black holes in the Einstein bumblebee gravity theory with spontaneous breaking of Lorentz symmetry caused by a nonzero vacuum expectation value of the vector field. We analyse corrections to black hole thermodynamics, including the non extensive Barrow entropy, parametrising quantum gravitational corrections to the Bekenstein Hawking area law. We introduce the York cavity formalism by placing the black hole in a finite isothermal cavi…

Does FOMC Tone Really Matter? Statistical Evidence from Spectral Graph Network Analysis
Jaeho Choi, Jaewon Kim, Seyoung Chung, Chae-shick Chung, Yoonsoo Lee
https://arxiv.org/abs/2510.02705

Does FOMC Tone Really Matter? Statistical Evidence from Spectral Graph Network Analysis
This study examines the relationship between Federal Open Market Committee (FOMC) announcements and financial market network structure through spectral graph theory. Using hypergraph networks constructed from S\&P 100 stocks around FOMC announcement dates (2011--2024), we employ the Fiedler value -- the second eigenvalue of the hypergraph Laplacian -- to measure changes in market connectivity and systemic stability. Our event study methodology reveals that FOMC announcements significantly alter…

Finite-blocklength Fluid Antenna Systems
Zhentian Zhang, Kai-Kit Wong, David Morales-Jimenez, Hao Jiang, Hao Xu, Christos Masouros, Zaichen Zhang, Chan-Byoung Chae
https://arxiv.org/abs/2509.15643

Finite-blocklength Fluid Antenna Systems
This work introduces and investigates finite blocklength fluid antenna systems (FBL-FASs). To meet the stringent key performance indicators (KPIs) of 6G and beyond networks, including ultra-massive machine-type communications (mMTC), ultra-reliable low-latency communications (URLLC), and enhanced mobile broadband (eMBB), it is necessary to evaluate the performance of FAS under limited channel uses across time, frequency, and other domains. By exploiting random matrix theory and extreme value th…

An objective criterion for evaluating new physical theories
Yefim Bakman
https://arxiv.org/abs/2509.16217 https://arxiv.org/pdf/2509.16217

An objective criterion for evaluating new physical theories
Currently, the value of a new physical theory is determined by whether it has been published in a prestigious journal. Yet, to publish an article in a prestigious journal, one must undergo a rigorous process of independent subjective peer review, with the success of the theory depending on the subjective opinion of reviewers who have proven themselves in developing old theories of physics. As a result, a closed system (gatekeeping) has been created that does not allow the penetration of new the…

On Dynamic Programming Theory for Leader-Follower Stochastic Games
Jilles Steeve Dibangoye, Thibaut Le Marre, Ocan Sankur, Fran\c{c}ois Schwarzentruber
https://arxiv.org/abs/2512.05667 https://arxiv.org/pdf/2512.05667 https://arxiv.org/html/2512.05667
arXiv:2512.05667v1 Announce Type: new
Abstract: Leader-follower general-sum stochastic games (LF-GSSGs) model sequential decision-making under asymmetric commitment, where a leader commits to a policy and a follower best responds, yielding a strong Stackelberg equilibrium (SSE) with leader-favourable tie-breaking. This paper introduces a dynamic programming (DP) framework that applies Bellman recursion over credible sets-state abstractions formally representing all rational follower best responses under partial leader commitments-to compute SSEs. We first prove that any LF-GSSG admits a lossless reduction to a Markov decision process (MDP) over credible sets. We further establish that synthesising an optimal memoryless deterministic leader policy is NP-hard, motivating the development of {\epsilon}-optimal DP algorithms with provable guarantees on leader exploitability. Experiments on standard mixed-motive benchmarks-including security games, resource allocation, and adversarial planning-demonstrate empirical gains in leader value and runtime scalability over state-of-the-art methods.
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Crosslisted article(s) found for cs.FL. https://arxiv.org/list/cs.FL/new
[1/1]:
- Determination of the fifth Busy Beaver value
The bbchallenge Collaboration, et al.

Gyromagnetic ratio and Pauli form factor in anisotropic QED$_{2 1}$ at one-loop
Susobhan Mandal, Subrata Mandal
https://arxiv.org/abs/2509.17082 https://…

Gyromagnetic ratio and Pauli form factor in anisotropic QED$_{2 + 1}$ at one-loop
The gyromagnetic ratio and Pauli form factor are important quantities that characterize the electric and magnetic moment distribution of a particle. The experimentally measured value for the gyromagnetic ratio or the spin g-factor of an electron in a vacuum agrees remarkably well with theoretical predictions, making it one of the biggest successes of quantum field theory. However, these factors may get modified compared to their vacuum counterparts due to the interaction present in the system. …

Replaced article(s) found for nucl-th. https://arxiv.org/list/nucl-th/new
[1/1]:
- Symmetry energy expansion and the peak value of the bulk viscosity
Steven P Harris