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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Motion Planning in a Society of Intelligent Mobile Agents

The majority of the work on this grant involved formal modeling of human-computer integration. We conceptualize computer resources as a multiagent system so that these resources and human collaborators may be modeled uniformly. In previous work we had used modal for this uniform modeling, and we had developed a process-algebraic agent abstraction. In this work, we applied this abstraction (using CSP) in uniformly modeling agents and users, which allowed us to use tools for investigating CSP models. This work revealed the power of, process-algebraic handshakes in modeling face-to-face conversation. We also investigated specifications of human-computer systems in the style of algebraic specification. This involved specifying the common knowledge required for coordination and process-algebraic patterns of communication actions intended to establish the common knowledge. We investigated the conditions for agents endowed with perception to gain common knowledge and implemented a prototype neural-network system that allows agents to detect when such conditions hold. The literature on multiagent systems conceptualizes communication actions as speech acts. We implemented a prototype system that infers the deontic effects (obligations, permissions, prohibitions) of speech acts and detects violations of these effects. A prototype distributed system was developed that allows users to collaborate in moving proxy agents; it was designed to exploit handshakes and common knowledge Finally. in work carried over from a previous NASA ARC grant, about fifteen undergraduates developed and presented projects on multiagent motion planning.

Esterline, Albert C.↗
NASA NTRS2002

IDEA: Planning at the Core of Autonomous Reactive Agents

Several successful autonomous systems are separated into technologically diverse functional layers operating at different levels of abstraction. This diversity makes them difficult to implement and validate. In this paper, we present IDEA (Intelligent Distributed Execution Architecture), a unified planning and execution framework. In IDEA a layered system can be implemented as separate agents, one per layer, each representing its interactions with the world in a model. At all levels, the model representation primitives and their semantics is the same. Moreover, each agent relies on a single model, plan database, plan runner and on a variety of planners, both reactive and deliberative. The framework allows the specification of agents that operate, within a guaranteed reaction time and supports flexible specification of reactive vs. deliberative agent behavior. Within the IDEA framework we are working to fully duplicate the functionalities of the DS1 Remote Agent and extend it to domains of higher complexity than autonomous spacecraft control.

Muscettola, Nicola↗
NASA NTRS2004

Product Distribution Theory for Control of Multi-Agent Systems

Product Distribution (PD) theory is a new framework for controlling Multi-Agent Systems (MAS's). First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint stare of the agents. Accordingly we can consider a team game in which the shared utility is a performance measure of the behavior of the MAS. For such a scenario the game is at equilibrium - the Lagrangian is optimized - when the joint distribution of the agents optimizes the system's expected performance. One common way to find that equilibrium is to have each agent run a reinforcement learning algorithm. Here we investigate the alternative of exploiting PD theory to run gradient descent on the Lagrangian. We present computer experiments validating some of the predictions of PD theory for how best to do that gradient descent. We also demonstrate how PD theory can improve performance even when we are not allowed to rerun the MAS from different initial conditions, a requirement implicit in some previous work.

Lee, Chia Fan↗
NASA NTRS2004

Ecology Based Decentralized Agent Management System

The problem of maintaining a desired number of mobile agents on a network is not trivial, especially if we want a completely decentralized solution. Decentralized control makes a system more r e bust and less susceptible to partial failures. The problem is exacerbated on wireless ad hoc networks where host mobility can result in significant changes in the network size and topology. In this paper we propose an ecology-inspired approach to the management of the number of agents. The approach associates agents with living organisms and tasks with food. Agents procreate or die based on the abundance of uncompleted tasks (food). We performed a series of experiments investigating properties of such systems and analyzed their stability under various conditions. We concluded that the ecology based metaphor can be successfully applied to the management of agent populations on wireless ad hoc networks.

Peysakhov, Maxim D.↗
NASA NTRS2006

Efficient Agent-Based Models for Non-Genomic Evolution

Modeling dynamical systems composed of aggregations of primitive proteins is critical to the field of astrobiological science involving early evolutionary structures and the origins of life. Unfortunately traditional non-multi-agent methods either require oversimplified models or are slow to converge to adequate solutions. This paper shows how to address these deficiencies by modeling the protein aggregations through a utility based multi-agent system. In this method each agent controls the properties of a set of proteins assigned to that agent. Some of these properties determine the dynamics of the system, such as the ability for some proteins to join or split other proteins, while additional properties determine the aggregation s fitness as a viable primitive cell. We show that over a wide range of starting conditions, there are mechanisins that allow protein aggregations to achieve high values of overall fitness. In addition through the use of agent-specific utilities that remain aligned with the overall global utility, we are able to reach these conclusions with 50 times fewer learning steps.

Gupta, Nachi↗
NASA NTRS2008

Transdermal delivery of therapeutic agent

A device for the transdermal delivery of a therapeutic agent to a biological subject that includes a first electrode comprising a first array of electrically conductive microprojections for providing electrical communication through a skin portion of the subject to a second electrode comprising a second array of electrically conductive microprojections. Additionally, a reservoir for holding the therapeutic agent surrounding the first electrode and a pulse generator for providing an exponential decay pulse between the first and second electrodes may be provided. A method includes the steps of piercing a stratum corneum layer of skin with two arrays of conductive microprojections, encapsulating the therapeutic agent into biocompatible charged carriers, surrounding the conductive microprojections with the therapeutic agent, generating an exponential decay pulse between the two arrays of conductive microprojections to create a non-uniform electrical field and electrokinetically driving the therapeutic agent through the stratum corneum layer of skin.

Kwiatkowski, Krzysztof C.↗
NASA NTRS2012

Effects of a Pedagogical Agent's Emotional Expressiveness on Learner Perceptions

The use of animated pedagogical agents or avatars in instruction has lagged behind their use in entertainment. This is due in part to the cost and complexity of development and implementation of agents in educational settings, but also results from a lack of research to understand how emotions from animated agents influence instructional effectiveness. The phenomenological study presented here assesses the perceptions of eight learners interacting with low and high intensity emotionally expressive pedagogical agents in a computer-mediated environment. Research methods include maximum variation and snowball sampling with random assignment to treatment. The resulting themes incorporate perceptions of importance, agent humanness, enjoyment, implementation barriers, and suggested improvements. Design recommendations and implications for future research are presented.

Romero, Enilda J.↗
NASA NTRS2012

Understanding Group/Party Affiliation Using Social Networks and Agent-Based Modeling

The dynamics of group affiliation and group dispersion is a concept that is most often studied in order for political candidates to better understand the most efficient way to conduct their campaigns. While political campaigning in the United States is a very hot topic that most politicians analyze and study, the concept of group/party affiliation presents its own area of study that producers very interesting results. One tool for examining party affiliation on a large scale is agent-based modeling (ABM), a paradigm in the modeling and simulation (M&S) field perfectly suited for aggregating individual behaviors to observe large swaths of a population. For this study agent based modeling was used in order to look at a community of agents and determine what factors can affect the group/party affiliation patterns that are present. In the agent-based model that was used for this experiment many factors were present but two main factors were used to determine the results. The results of this study show that it is possible to use agent-based modeling to explore group/party affiliation and construct a model that can mimic real world events. More importantly, the model in the study allows for the results found in a smaller community to be translated into larger experiments to determine if the results will remain present on a much larger scale.

Campbell, Kenyth↗
NASA NTRSDate not supplied

SafeMAP: Safe Multi-Agent Planning Framework Based on Dynamic Probabilistic Risk Assessment

This paper proposes a risk-aware framework for Safe Multi-Agent Planning (SafeMAP) that unifies disparate models for multi-agent systems in a Markovian process that allows for simultaneous system health monitoring, decision making under uncertainty, and multi-agent system collaboration. As operations beyond low earth orbit mature, there is an increased need for autonomous cyber-physical systems with onboard decision making capabilities. Multi-agent cyber-physical systems in particular offer the potential of increased efficiency, resiliency, and mission capabilities for future applications such as multi-rover terrain operations, distributed satellite operations, and management of smart lunar habitats. SafeMAP utilizes physics-based models of each agent and the relevant components, probability models of the environment and component operational states, and reward models for mission-specific objectives such as scientific task completion or resource consumption. The output of SafeMAP is a set of mission plans that satisfy the mission objective under specified risk/reward constraints. A readable interpretation of each of these generated mission plans is provided as an additional output. SafeMAP has been demonstrated on a simulated case study involving a four-rover system performing surface mapping operations and science tasks. Results of this paper demonstrate SafeMAP’s ability to generate explainable mission plans that satisfy the mission objective while minimizing risk under nominal and off-nominal conditions.

Mohammad Hejase↗
NASA NTRSDate not supplied

SafeMAP: Safe Multi-Agent Planning framework based on Dynamic Probabilistic Risk Assessment

This paper proposes a risk-aware framework for Safe Multi-Agent Planning (SafeMAP) that unifies disparate models for multi-agent systems in a Markovian process that allows for simultaneous system health monitoring, decision making under uncertainty, and multi-agent system collaboration. As operations beyond low earth orbit mature, there is an increased need for autonomous cyber-physical systems with onboard decision making capabilities. Multi-agent cyber-physical systems in particular offer the potential of increased efficiency, resiliency, and mission capabilities for future applications such as multi-rover terrain operations, distributed satellite operations, and management of smart lunar habitats. SafeMAP utilizes physics-based models of each agent and the relevant components, probability models of the environment and component operational states, and reward models for mission-specific objectives such as scientific task completion or resource consumption. The output of SafeMAP is a set of mission plans that satisfy the mission objective under specified risk/reward constraints. A readable interpretation of each of these generated mission plans is provided as an additional output. SafeMAP has been demonstrated on a simulated case study involving a four-rover system performing surface mapping operations and science tasks. Results of this paper demonstrate SafeMAP’s ability to generate explainable mission plans that satisfy the mission objective while minimizing risk under nominal and off-nominal conditions.

Mohammad Hejase↗
DOE OSTI2021

Enhanced oxygen transfer agent systems for oxidative dehydrogenation of hydrocarbons

Aspects of the invention relate to enhanced oxygen transfer agent systems and methods of use thereof. According to one aspect, a method for producing olefins from a hydrocarbon feed includes the step of contacting a hydrocarbon feed comprised of one or more alkanes with an oxygen transfer agent at a temperature of 350° C. to 1000° C. The oxygen transfer agent comprising an oxygen-donating chalcogen agent comprised of at least one of S, Se, or Te and a reducible metal oxide. The chalcogen having an oxidation state greater than +2. According to another aspect, a method for producing one or more olefins by partial combustion of a hydrocarbon feed includes partially combusting a hydrocarbon feed comprised of one or more alkanes by contacting the hydrocarbon feed with an oxygen transfer agent comprising CaS04 at a temperature of 350° C. to 1000° C. to produce one or more olefins comprising ethylene and coproducing water.

Sofranko, John A.↗
DOE OSTI2022

Enhanced oxygen transfer agent systems for oxidative dehydrogenation of hydrocarbons

Enhanced oxygen transfer agent systems and methods of use thereof are provided. According to one aspect, a method for producing olefins from a hydrocarbon feed includes the step of contacting a hydrocarbon feed comprised of one or more alkanes with an oxygen transfer agent at a temperature of 350° C. to 1000° C. The oxygen transfer agent includes an oxygen-donating chalcogen agent including at least one of S, Se, or Te and a reducible metal oxide. The chalcogen has an oxidation state greater than +2. A method for producing one or more olefins by partial combustion of a hydrocarbon feed is provided. The method includes partially combusting a hydrocarbon feed comprised of one or more alkanes by contacting the hydrocarbon feed with an oxygen transfer agent comprising CaSO 4 at a temperature of 350° C. to 1000° C. to produce one or more olefins comprising ethylene and coproducing water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Chemical and Foaming Stability of Foam Decontaminating Agents - 16137

This study conducted experiments to evaluate the stability of nano foaming agents by adding various types of surfactants, silica nanoparticles, and viscosifiers with the aim of enhancing the stability of foaming agents containing nanoparticles. Nonionic surfactants such as EM100 showed higher stability as compared to the Sodium Dodecyl Sulfate (SDS) anionic surfactant, and the foam stability decreased as the surfactant concentration increased. The co-surfactant addition did not significantly affect the foam stability, but the addition of Xantan gum-one of the various viscosifiers tested in this study-resulted in the highest foam stability. When silica nanoparticles were added to the surfactant EM100, the foam stability improved further. In particular, the foam stability of the nano foaming agent was observed to be the maximum when a partially hydrophobic nano-porous silica such as KAERI 1 was added, as compared to the addition of a hydrophilic dry silica such as M5. This is because the partially hydrophobic particles were distributed over the liquid film between the foams, thereby preventing drainage and increasing the stability of the foaming agent fluid. The manufactured nano foaming agent can be used not only for the effective decontamination of large-sized equipment or large facilities but also for overcoming the problem of production of a large amount of radioactive waste during chemical decontamination. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Towards Agentic AI on Particle Accelerators

As particle accelerators grow in complexity, traditional control methods face increasing challenges in achieving optimal performance. This paper envisions a paradigm shift: a decentralized multi-agent framework for accelerator control, powered by Large Language Models (LLMs) and distributed among autonomous agents. We present a proposition of a self-improving decentralized system where intelligent agents handle high-level tasks and communication and each agent is specialized control individual accelerator components. This approach raises some questions: What are the future applications of AI in particle accelerators? How can we implement an autonomous complex system such as a particle accelerator where agents gradually improve through experience and human feedback? What are the implications of integrating a human-in-the-loop component for labeling operational data and providing expert guidance? We show two examples, where we demonstrate viability of such architecture.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Agentic Diagrammatica: Towards Autonomous Symbolic Computation in High Energy Physics

We present Diagrammatica, a symbolic computation extension to the HEPTAPOD agentic framework, which enables LLM agents to plan and execute multi-step theoretical calculations. Symbolic computation poses a distinctive reliability challenge for LLM agents, as correctness is governed by implicit mathematical conventions that are not encoded in a form that can be easily checked in the computational backend. We identify two complementary remedies, tool-constrained computation and targeted knowledge grounding, and pursue the first as the primary architecture. Concretely, we concentrate the agent's action distribution onto tool calls with convention-fixing semantics, in which the agent specifies a compact, human-auditable diagram specification and a trusted backend performs the symbolic or numerical manipulations exactly. The toolkit provides two complementary calculation paths consuming a shared diagram specification: Naive Dimensional Analysis (NDA) for order-of-magnitude rate estimates and Exact Diagrammatic Analysis (EDA) for tree-level symbolic calculations via automatic FeynCalc code generation, both supplemented by automatic Feynman diagram enumeration and a navigable theory knowledge base. The architecture is validated on two benchmarks: (1) an exhaustive catalog of all tree-level, single-vertex $1\to 2$ partial decay widths across scalar, fermion, and vector parents, with complete massless and threshold limits and Standard Model validation; and (2) an NDA sensitivity study of the muon decay multiplicity $μ^+ \to ν_μ\barν_e + n(e^+e^-) + e^-$, determining the maximum observable $n$ at current and planned muon experiments.

Menzo, Tony [Alabama U.; Fermilab] (ORCID:00000002↗
DOE OSTI2016

Effective methylation of phosphonic acids related to chemical warfare agents mediated by trimethyloxonium tetrafluoroborate for their qualitative detection and identification by gas chromatography-mass spectrometry

The effective methylation of phosphonic acids related to chemical warfare agents (CWAs) employing trimethyloxonium tetrafluoroborate (TMO·BF 4 ) for their qualitative detection and identification by gas chromatography-mass spectrometry (GC-MS) is presented. The methylation occurs in rapid fashion (1 h) and can be conveniently carried out at ambient temperature, thus providing a safer alternative to the universally employed diazomethane-based methylation protocols. Optimization of the methylation parameters led us to conclude that methylene chloride was the ideal solvent to carry out the derivatization, and that even though methylated products can be observed surfacing after only 1 h, additional time was not found to be detrimental but beneficial to the process particularly when dealing with analytes at low concentrations (~10 μg mL -1 ). Due to its insolubility in methylene chloride, TMO·BF 4 conveniently settles to the bottom during the reaction and does not produce additional interfering by-products that may further complicate the GC-MS analysis. We demonstrated the method to successfully methylate a variety of Schedule 2 phosphonic acids, including their half esters, resulting in derivatives that were readily detected and identified using the instrument's spectral library. Most importantly, the method was shown to simultaneously methylate a mixture of the organophosphorus-based nerve agent hydrolysis products: pinacolyl methylphosphonate (PMPA), cyclohexyl methylphosphonate (CyMPA) and ethyl methylphosphonate (EMPA) (at a 10 μg mL - 1 concentration each) in a fatty acid ester-rich organic matrix (OPCW-PT-O 3 ) featured in the 38th Organisation for the Prohibition of Chemical Weapons (OPCW) Proficiency Test. Additionally, the protocol was found to effectively methylate N,N-diethylamino ethanesulfonic acid and N,N-diisopropylamino ethanesulfonic acid that are products arising from the oxidative degradation of the V-series agents VR and VX respectively. This work described herein represents the first report on the use of TMO·BF 4 as a viable, stable and safe agent for the methylation of phosphonic acids and their half esters and within the context of an OPCW Proficiency Test sample analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multi-level impacts of climate change and supply disruption events on a potato supply chain: An agent-based modeling approach

Context: The world is experiencing frequent extreme weather events like droughts, snowstorms, and shifting of seasons due to climate change. Increased frequency and severity of these extreme weather events threaten food security because agriculture depends on climate conditions. Impacts of climate change on the agricultural system not only occur at the grower’s level, but also cascade to other levels along the supply chain. Objective: In this study, we aim to quantify a wide range of economic impacts of different extreme climate events on different stages of a food supply chain. Methods: We chose the potato supply chain in Idaho as a case study. We developed a multi-echelon supply chain simulation model using an agent-based modeling (ABM) approach with five types of agents—farmers, shippers, processors, retailers, and logistics companies. In addition to the business-as-usual (BAU) scenario, we designed two climate-related disruption events—drought and snowstorm. We quantified the heterogeneous impacts at different stages of the supply chain for both fresh and processed potatoes using key performance indicators (KPIs) including revenues, prices, lead times, traded quantities, and food waste quantity. Results and Conclusion: The impacts of the disruption events are different on different agents in the supply chain for different product categories. The price hike of fresh potatoes is far higher than processed potatoes during disruption events. This price hike makes consumers switch to processed potatoes, which require more fresh potatoes as an input that further reinforces the price hike. However, because processed potatoes have an elastic demand, once their prices go up due to higher input cost, their demand drops. Non-contracted farmers gain additional revenues from the disruption events, whereas contracted farmers incur a loss due to lock-in price and lower than usual harvest. Significance: The methodology developed in this study could be applied to other food and agricultural supply chains for understanding the vulnerabilities at agent levels due to climate change disruption events. Furthermore, the findings would help develop mitigation strategies or policies to improve the well-being of the overall supply chain.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Agentic traffic intelligence: Augmented human-in-the-loop scenario generation for microscopic traffic simulation

Traditional microscopic traffic simulation generation often relies on static datasets and manual design, limiting its ability to simulate complex conditions easily. This paper presents a novel framework, Agentic Traffic Intelligence, which combines human approval large language models (LLMs), the Real-Twin tool, and multi-agent systems to perform realistic microscopic traffic simulation scenario generation. The proposed framework incorporates human-in-the-loop (HIL) control, retrieval-augmented generation (RAG), and multi-agent control mechanisms. HIL mechanisms are used to guide multiple LLMs focused on attributes for microscopic simulation generation and to improve the interpretability and transparency of LLM execution for users. RAG enhances context extraction by dynamically integrating external knowledge sources for traffic scenario generation foundations. A multi-agent architecture with supervisory control coordinates the interaction of simulation components, including traffic simulators, control logic, and calibration tools. This enables the synthesis of simulation-ready scenarios that reflect dynamic demand profiles and behavior controls. Furthermore, the framework fuses multisource traffic data with unstructured context and supports iterative refinement through interactive user feedback. Validated through microscopic simulation using Simulation of Urban Mobility, the generated scenarios demonstrate high-fidelity network generation with inflow and turn movement and behavioral calibration, offering a robust and efficient tool for stress-testing and optimizing urban mobility systems.

Hierarchical multi-agent control↗