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K. Suzanne Barber

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11 papers
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11

AAMAS Conference 2007 Conference Paper

Dynamically Learning Sources of Trust Information: Experience vs. Reputation

  • Karen K. Fullam
  • K. Suzanne Barber

Trust is essential when an agent must rely on others to provide resources for accomplishing its goals. When deciding whether to trust, an agent may rely on, among other types of trust information, its past experience with the trustee or on reputations provided by third-party agents. However, each type of trust information has strengths and weaknesses: trust models based on past experience are more certain, yet require numerous transactions to build, while reputations provide a quick source of trust information, but may be inaccurate due to unreliable reputation providers. This research examines how the accuracy of experience- and reputationbased trust models is influenced by parameters such as: frequency of transactions with the trustee, trustworthiness of the trustee, and accuracy of provided reputations. More importantly, this research presents a technique for dynamically learning the best source of trust information given these parameters. The demonstrated learning technique achieves payoffs equal to those achieved by the best single trust information source (experience or reputation) in nearly every scenario examined.

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JAAMAS Journal 2006 Journal Article

Adaptive decision-making frameworks for dynamic multi-agent organizational change

  • Cheryl Martin
  • K. Suzanne Barber

Abstract This article presents a capability called Adaptive Decision-Making Frameworks (ADMF) and shows that it can result in significantly improved system performance across run-time situation changes in a multi-agent system. Specifically, ADMF can result in improved and more robust performance compared to the use of a single static decision-making framework (DMF). The ADMF capability allows agents to dynamically adapt the DMF in which they participate to fit their run-time situation as it changes. A DMF identifies a set of agents and specifies the distribution of decision-making control and the authority to assign subtasks among these agents as they determine how a goal or set of goals should be achieved. The ADMF capability is a form of organizational adaptation and differs from previous approaches to organizational adaptation and dynamic coordination in that it is the first to allow dynamic and explicit manipulation of these DMF characteristics at run-time as variables controlling agent behavior. The approach proposed for selecting DMFs at run-time parameterizes all domain-specific knowledge as characteristics of the agents’ situation, so the approach is application-independent. The presented evaluation empirically shows that, for at least one multi-agent system, there is no one best DMF for multiple agents across run-time situational changes. Next, it motivates the further exploration of ADMF by showing that adapting DMFs to run-time variations in situation can result in improved overall system performance compared to static or random DMFs.

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AAAI Conference 2000 Conference Paper

The Systems Engineering Process Activities (SEPA) Methodology and Tool Suite

  • K. Suzanne Barber
  • Paul Grisham
  • and Sutirtha Bhattacharya

The Sensible Agent Testbed allows users to perform controlled and repeatable experiments on the performance of Sensible Agents in a distributed simulation environment. The testbed uses CORBA(R) and IDL(R) to connect modules running in C++, ModSim, Java, and Lisp on WindowsNT and Linux platforms. Users can perform initialization, monitoring, and logging of the environment or individual Sensible Agent performance as the simulation progresses. Several different scenarios are presented to demonstrate the capabilities of Sensible Agents in a Naval Radar Frequency Management domain. Sensible Agents can use Dynamic Adaptive Autonomy (DAA) to adapt the structure of their problem-solving organizations in order to handle the complex and dynamic nature of this domain. Users can view this adaptation and monitor related system and agent performance variables as the simulation runs. This technology has the potential to provide advanced multi-agent capabilities to legacy planners with a minimal recoding effort.

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ICRA Conference 1997 Conference Paper

An approach for monitoring and control of agent-based systems

  • Srini Ramaswamy
  • A. Suraj
  • K. Suzanne Barber

Finite state machines and their extensions are widely used for system modeling and analysis. Often, the models themselves do not provide much insight into critical system areas which need to be observed (or monitored) for effective control. The issue is mostly left to the discretion of the development team which often has limited domain knowledge. In this paper, an effective method to identify necessary critical system areas that need to be observed and those areas that lead example to the identification of varying levels of control in a design model are discussed. Also, the applicability of this method in differentiating and choosing between two similar system designs is discussed. Extended Statecharts (ESCs) that exploit the XOR configuration of Statecharts for system failure modeling are used for developing the high level system model. The ESC model is subsequently transformed into a high level Petri net model and Petri net analysis techniques are used for the identification of critical system areas for observation and control as well as to differentiate between nearly identical ESC system models.

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ICRA Conference 1995 Conference Paper

APE: An Experience-Based Assembly Sequence Planner for Mechanical Assemblies

  • Anand Swaminathan
  • K. Suzanne Barber

This paper presents an approach to the assembly sequence planning problem based on a "plan reuse" philosophy, called the Assembly Planner using Experience (APE). Assembly planning research in the past has attempted to completely plan each problem from scratch. This research shows that stored cases of basic assembly configurations can be applied to a given assembly problem. It is observed that the number of such basic assembly configurations is quite small. Constraints affecting the assembly are also explicitly handled.

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ICRA Conference 1995 Conference Paper

OARS: An Object-Oriented Architecture for Reactive Systems

  • Bernard T. Barcio
  • Srini Ramaswamy
  • K. Suzanne Barber

This paper discusses an architecture designed to provide support for the development of state transition models for an object-oriented distributed environment. The state transition models can be constructed and specified hierarchically as well as derived into new classes of objects through the use of inheritance. A new concept called "exit-safe states" is introduced to assist in the specification of hierarchical state transition models. A graphical monitor to analyze the system at run time has been developed.

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ICRA Conference 1987 Conference Paper

Analysis of human communication during assembly tasks

  • K. Suzanne Barber
  • Gerald J. Agin

This paper studies human-to-human interaction in an attempt to reveal the kinds of human-to-machine interaction that will be necessary for intelligent robot learning of assembly tasks. Experiments were performed in which an "expert" guided an "apprentice" through a complex assembly task using spoken language but no visual communication. An analysis of the dialog reveals that certain protocols and conventions facilitate communication, and that communication breaks down when these protocols are not observed. Five types of protocols were observed: focusing, validators, referencing, descriptors and dialog structure. The implications of these results for human-robot communication are discussed.

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