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At least 91 records · Page 5

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.↗

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↗

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↗

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.↗

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↗

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.↗

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.↗

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↗

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↗

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↗

Development of high temperature resistant graphite fiber coupling agents

Surface treatments were investigated as potential coupling agents to improve the elevated temperature shear strength retention of polyimide/graphite and polyphenylquinoxaline/graphite composites. The potential coupling agents were evaluated by fiber strand tensile tests, fiber and composite weight losses at 533 and 588K, and by interlaminar shear strength retention at 533 and 588K. The two surface treatments selected for more extensive evaluation were a coating of Ventromer T-1, a complex organometallic reaction product of titanium tetrachloride and trimethyl borate, and a polyphenylquinoxaline (PPQ) sizing which was pyrolyzed in nitrogen to form a carbonaceous layer on the fiber. Pyrolyzed polyphenylquinoxaline is a satisfactory coupling agent for polyimide/Thornel 300 graphite fiber composites. During 1000 hours aging at 588K such composites lose a little over half their transverse tensile strength, and suffer a slight loss in flexural modulus. No degradation of flexural strength or interlaminar shear strength occured during 1000 hours aging at 588K. None of the coupling agents examined had a markedly beneficial effect with polyphenylquinoxaline composites.

Griffin, R. N.↗

Spacecraft disinfectant/cleansing agent development

The sanitation agent container, which was selected in a trade off study, employs two chambers, a rigid outer container and an inner flexible bladder. The bladder contains the sanitation agent formulation and its release is controlled by a manually operated valve. The outer container holds a high pressure vapor. There is no void in the bladder which makes the package operation independent of orientation and therefore usable in zero gravity. Foam is developed by a low boiling point fluid or dissolved in the product. When the product is dispensed at atmospheric presure, the evolved gas or vapor whips up a goam in the valve. The sanitation agents were initially formulated with freons which produces an excellent foam. However freon is incompatible with the life support system and was replaced with carbon dioxide dissolved at high pressure. The CO2 system may limit high temperature exposure to prevent leakage or package distortion. The sanitation agents have been shown to be effective in cleaning soils from personnel and material.

Abbate, M.↗

Agent oriented programming

The goal of our research is a methodology for creating robust software in distributed and dynamic environments. The approach taken is to endow software objects with explicit information about one another, to have them interact through a commitment mechanism, and to equip them with a speech-acty communication language. System-level applications include software interoperation and compositionality. A government application of specific interest is an infrastructure for coordination among multiple planners. Daily activity applications include personal software assistants, such as programmable email, scheduling, and new group agents. Research topics include definition of mental state of agents, design of agent languages as well as interpreters for those languages, and mechanisms for coordination within agent societies such as artificial social laws and conventions.

Shoham, Yoav↗

Research and Development for an Operational Information Ecology: The User-System Interface Agent Project

The User System Interface Agent (USIA) is a special type of software agent which acts as the "middle man" between a human user and an information processing environment. USIA consists of a group of cooperating agents which are responsible for assisting users in obtaining information processing services intuitively and efficiently. Some of the main features of USIA include: (1) multiple interaction modes and (2) user-specific and stereotype modeling and adaptation. This prototype system provides us with a development platform towards the realization of an operational information ecology. In the first phase of this project we focus on the design and implementation of prototype system of the User-System Interface Agent (USIA). The second face of USIA allows user interaction via a restricted query language as well as through a taxonomy of windows. In third phase the USIA system architecture was revised.

Srivastava, Sadanand↗

Emergent Aerospace Designs Using Negotiating Autonomous Agents

This paper presents a distributed design methodology where designs emerge as a result of the negotiations between different stake holders in the process, such as cost, performance, reliability, etc. The proposed methodology uses autonomous agents to represent design decision makers. Each agent influences specific design parameters in order to maximize their utility. Since the design parameters depend on the aggregate demand of all the agents in the system, design agents need to negotiate with others in the market economy in order to reach an acceptable utility value. This paper addresses several interesting research issues related to distributed design architectures. First, we present a flexible framework which facilitates decomposition of the design problem. Second, we present overview of a market mechanism for generating acceptable design configurations. Finally, we integrate learning mechanisms in the design process to reduce the computational overhead.

Deshmukh, Abhijit↗

Multi-Agent Diagnosis and Control of an Air Revitalization System for Life Support in Space

An architecture of interoperating agents has been developed to provide control and fault management for advanced life support systems in space. In this adjustable autonomy architecture, software agents coordinate with human agents and provide support in novel fault management situations. This architecture combines the Livingstone model-based mode identification and reconfiguration (MIR) system with the 3T architecture for autonomous flexible command and control. The MIR software agent performs model-based state identification and diagnosis. MIR identifies novel recovery configurations and the set of commands required for the recovery. The AZT procedural executive and the human operator use the diagnoses and recovery recommendations, and provide command sequencing. User interface extensions have been developed to support human monitoring of both AZT and MIR data and activities. This architecture has been demonstrated performing control and fault management for an oxygen production system for air revitalization in space. The software operates in a dynamic simulation testbed.

Malin, Jane T.↗

Collaborative Information Agents on the World Wide Web

In this paper, we present DIAMS, a system of distributed, collaborative information agents which help users access, collect, organize, and exchange information on the World Wide Web. Personal agents provide their owners dynamic displays of well organized information collections, as well as friendly information management utilities. Personal agents exchange information with one another. They also work with other types of information agents such as matchmakers and knowledge experts to facilitate collaboration and communication.

Chen, James R.↗

Designing Agent Collectives For Systems With Markovian Dynamics

The "Collective Intelligence" (COIN) framework concerns the design of collectives of agents so that as those agents strive to maximize their individual utility functions, their interaction causes a provided "world" utility function concerning the entire collective to be also maximized. Here we show how to extend that framework to scenarios having Markovian dynamics when no re-evolution of the system from counter-factual initial conditions (an often expensive calculation) is permitted. Our approach transforms the (time-extended) argument of each agent's utility function before evaluating that function. This transformation has benefits in scenarios not involving Markovian dynamics, in particular scenarios where not all of the arguments of an agent's utility function are observable. We investigate this transformation in simulations involving both linear and quadratic (nonlinear) dynamics. In addition, we find that a certain subset of these transformations, which result in utilities that have low "opacity (analogous to having high signal to noise) but are not "factored" (analogous to not being incentive compatible), reliably improve performance over that arising with factored utilities. We also present a Taylor Series method for the fully general nonlinear case.

Wolpert, David H.↗