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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Electricity Market Dynamics as Smooth Games: Organizing Gradient-Based Learners and Identifying Instabilities

Wide-spread adoption of machine learning and distributed energy production has the potential to fundamentally change behaviours of energy markets. In practice, along with the benefits, previously unseen instabilities have begun emerging in markets currently embracing these technologies. In this report we study electricity markets as dynamical systems arising in smooth games, where energy consumers are modelled as gradient-based learners who interact on a graph through distributed energy producers. We give simple examples of how instabilities can arise even when the consumers’ local objectives seem reasonable and how these instabilities can be remedied. Drawing insights from these examples, we begin developing a general model of optimization-driven electricity market dynamics and give conditions for ensuring local Nash equilibria of the system are stable fixed points of the dynamics. Our results demonstrate how models of electricity market dynamics might be used for deriving formal guarantees in order to stabilize markets and enact regulatory policies in the face of market shocks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Game-Theoretic Strategies for Quantum-Conventional Network Infrastructures

Fundamentally and practically, quantum networks and conventional networks are inextricably tied, since the basic quantum protocols such as teleportation require both networks and the conventional network fiber is also used for the quantum network. A Recursive System of Systems (RSOS) model is developed for quantum-conventional (QC) networks by modeling the correlations at various levels based on the failure and attack modes of quantum, conventional and hybrid components and the propagative effects across QC boundaries. A game-theoretic formulation is developed to capture the cost-benefit trade-offs of the provider in defending against component attacks, using sum-form utility functions. By applying the Nash Equilibrium results, the conditions and sensitivity functions of the survivalprobabilities of a QC network at different levels are derived using the strong dependencies between quantum and conventional infrastructures. The results provide insights into the dependenciesbetween conventional and quantum networks, including cross QC boundary effects in terms of disruption impact of conventional networks on quantum networks, and vice versa.

Rao, Nageswara↗
DOE OSTI2025

Foveal vision reduces neural resources in agent-based game learning

Efficient processing of information is crucial for the optimization of neural resources in both biological and artificial visual systems. In this paper, we study the efficiency that may be obtained via the use of a fovea. Using biologically-motivated agents, we study visual information processing, learning, and decision making in a controlled artificial environment, namely the Atari Pong video game. We compare the resources necessary to play Pong between agents with and without a fovea. Our study shows that a fovea can significantly reduce the neural resources, in the form of number of neurons, number of synapses, and number of computations, while at the same time maintaining performance at playing Pong. To our knowledge, this is the first study in which an agent must simultaneously optimize its visual system, along with its decision making and action generation capabilities. That is, the visual system is integral to a complete agent.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Game Strategies for Entanglement Paths in Quantum Network Infrastructure

Entanglement distribution is a core function of quantum networks, and the paths used for this purpose are composed of quantum and conventional network components and are routed through physical facility sites. A game theoretic model is formulated for the defense of entanglement paths in a quantum network infrastructure by modeling the correlations and probabilities of reinforcement and failure of its components. A sum-form utility function is used to capture the cost-benefit trade-offs in reinforcing the entanglement path components to defend against their failures and attacks. Under Nash Equilibrium criteria, estimates of survival probabilities of entanglement paths are derived using the parameters and correlations of quantum, conventional, hybrid, and facility components. They provide insights into the dependencies of entanglement paths on its components, including cross-boundary effects of conventional, quantum, and facility components.

Rao, Nageswara [ORNL] (ORCID:0000000234085941)↗
DOE OSTI2022

The role of information structures in game-theoretic multi-agent learning

Multi-agent learning (MAL) studies how agents learn to behave optimally and adaptively from their experience when interacting with other agents in dynamic environments. The outcome of a MAL process is jointly determined by all agents’ decision-making. Hence, each agent needs to think strategically about others’ sequential moves, when planning future actions. The strategic interactions among agents makes MAL go beyond the direct extension of single-agent learning to multiple agents. With the strategic thinking, each agent aims to build a subjective model of others decision-making using its observations. Such modeling is directly influenced by agents’ perception during the learning process, which is called the information structure of the agent’s learning. As it determines the input to MAL processes, information structures play a significant role in the learning mechanisms of the agents. This review creates a taxonomy of MAL and establishes a unified and systematic way to understand MAL from the perspective of information structures. Here we define three fundamental components of MAL: the information structure (i.e., what the agent can observe), the belief generation (i.e., how the agent forms a belief about others based on the observations), as well as the policy generation (i.e., how the agent generates its policy based on its belief). In addition, this taxonomy enables the classification of a wide range of state-of-the-art algorithms into four categories based on the belief-generation mechanisms of the opponents, including stationary, conjectured, calibrated, and sophisticated opponents. We introduce Value of Information (VoI) as a metric to quantify the impact of different information structures on MAL. Finally, we discuss the strengths and limitations of algorithms from different categories and point to promising avenues of future research.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Path integral games with de Sitter α-vacua

The α-vacua are a 1-parameter family of quantum field vacua in de Sitter space which are invariant under the isometry group SO(1, d). In this work give a path integral construction of the de Sitter α-vacua. We explain that these states can be prepared by acting on the Bunch-Davies vacuum with a certain non-local charge operator. While most conserved charges live on a single codimension-1 manifold, we show that this particular charge lives on a pair of two codimension-1 manifolds which are antipodal mirrors of each other. The rules for the manipulation of this charge as an insertion in the path integral are explained. We further explain how this charge can be used to solve for the wavefunctionals of the α-vacua at $\mathcal{I}$ | (in the regime that α is small) by deforming the equator of de Sitter space to $\mathcal{I}$ + /$\mathcal{I}$ – .

Global Symmetries↗
DOE OSTI2022

Editorial for the Virtual Special Issue of Journal of Power Sources “Low temperature fuel cells and electrolysers” - Science and engineering: Let's play this game hand in hand!

Electrochemistry is already and will increasingly be amongst the major drivers of our energetic mix decarbonization, so to fight anthropogenic global warming. The hydrogen economy vector (ideally produced in water electrolysers using renewable electricity and transformed back into electricity in fuel cells), in parallel with the conversion of carbon dioxide and nitrogen gas into value-added products are seen as pillars of the so-called green and sustainable Energy Revolution. The hydrogen technologies presently attract increasing interest, their momentum growing irremediably in Europe, Asia and Americas. Here, this Virtual Special Issue (VSI) gathers the latest scientific results of major research laboratories worldwide, all addressing various aspects of electrochemical energy and material conversion processes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Identifying Key Drivers of Wildfires in the Contiguous US Using Machine Learning and Game Theory Interpretation

Abstract Understanding the complex interrelationships between wildfire and its environmental and anthropogenic controls is crucial for wildfire modeling and management. Although machine learning (ML) models have yielded significant improvements in wildfire predictions, their limited interpretability has been an obstacle for their use in advancing understanding of wildfires. This study builds an ML model incorporating predictors of local meteorology, land‐surface characteristics, and socioeconomic variables to predict monthly burned area at grid cells of 0.25° × 0.25° resolution over the contiguous United States. Besides these predictors, we construct and include predictors representing the large‐scale circulation patterns conducive to wildfires, which largely improves the temporal correlations in several regions by 14%–44%. The Shapley additive explanation is introduced to quantify the contributions of the predictors to burned area. Results show a key role of longitude and latitude in delineating fire regimes with different temporal patterns of burned area. The model captures the physical relationship between burned area and vapor pressure deficit, relative humidity (RH), and energy release component (ERC), in agreement with the prior findings. Aggregating the contribution of predictor variables of all the grids by region, analyses show that ERC is the major contributor accounting for 14%–27% to large burned areas in the western US. In contrast, there is no leading factor contributing to large burned areas in the eastern US, although large‐scale circulation patterns featuring less active upper‐level ridge‐trough and low RH two months earlier in winter contribute relatively more to large burned areas in spring in the southeastern US.

54 ENVIRONMENTAL SCIENCES↗