K. S. Barber

JAAMAS Journal 2026 Journal Article

Infrastructure for Design, Deployment and Experimentation of Distributed Agent-based Systems: The Requirements, The Technologies, and An Example

• K. S. Barber
• A. Goel
• R. McKay

Abstract This paper discusses infrastructure for design, development, and experimentation of multi-agent systems. Multi-agent system design requires determining (1) how domain requirements drive the use of agents and AI techniques, (2) what competencies agents need in a MAS, and (3) which techniques implement those competencies. Deployment requirements include code reuse, parallel development through formal standardized object specifications, multi-language and multi-platform support, simulation and experimentation facilities, and user interfaces to view internal module, agent, and system operations. We discuss how standard infrastructure technologies such as OMG IDL, OMG CORBA, Java, and VRML support these services. Empirical evaluation of complex software systems requires iteration through combinations of experimental parameters and recording desired data. Infrastructure software can ease the setup, running, and analysis of large-scale computational experiments. The development of the Sensible Agent Testbed and architecture over the past six years provides a concrete example. The design rationale for the Sensible Agent architecture emphasizes domain-independent requirements and rapid deployment to new application domains. The Sensible Agent Testbed is a suite of tools providing or assisting in setting up, running, visually monitoring, and chronicling empirical testing and operation of complex, distributed multi-agent systems. A thorough look at the various Sensible Agents infrastructure pieces illustrates the engineering principles essential for multi-agent infrastructure, while documenting the software for users.

AAMAS Conference 2007 Conference Paper

Agent Trust Evaluation and Team Formation in Heterogeneous Organizations

• K. S. Barber
• J. Ahn
• S. Budalakoti
• D. DeAngelis
• K. K. Fullam
• C. L. D. Jones
• X. Sui

This demonstration highlights different aspects of the bottom-up assembly of multi-agent teams; illustrating trust evaluation of potential partners via experience- and reputation-based trust models, multi-dimensional trust evaluation of potential partners, task selection through personality-based modeling and team selection strategies that maximize a team's ability to function in dynamic environments. The demonstration format will be a software live demo with supporting slide shows.

AAAI Conference 2004 System Paper

Multi-Agent System Development: Design, Runtime, and Analysis

• K. S. Barber
• K. Fullam
• N. Gujral
• D. N. Lam
• J. Park

Dynamic and unexpected events are defining characteristics of numerous application domains. These environments often require decision-makers to solve many problems with insufficient time and resources. To effectively assess options, decision-makers require situation analysis and decision-support tools that model the dynamism of these environments to make rapid, robust decisions. Autonomous agents and multi-agent systems satisfy these requirements for decision-making in dynamic environments. Developing a multi-agent system (MAS) is a challenging task, considering sophisticated agent interactions and uncertain environmental dynamics and domain requirements. This demonstration addresses the comprehensive development process for multi-agent systems; illustrating tools for the initial design of the agent system, the capabilities encoded in the individual agents, and analysis tools that enhance developer comprehension of system behavior.

AAMAS Conference 2004 Conference Paper

Using Policies for Information Valuation to Justify Beliefs

• Karen Fullam
• K. S. Barber

AAAI Conference 2000 Conference Paper

Sensible Agents: Demonstration of Dynamic Adaptive Autonomy

• K. S. Barber
• D. C. Han
• D. N. Lam
• C. E. Martin

The analysis and design of large, complex systems mandates a formal methodology and supporting tools to assist system development teams throughout the system lifecycle. The multitude of personnel, the diversity of viewpoints, and the transient nature of personnel and technology in relation to the system lifecycle constrains the process by which 1) application domain requirements are acquired, analyzed and modeled, 2) a system architecture is derived from those requirements, 3) technology decisions are made and implementation progresses, and 4) the system is tested and maintained. A formal methodology for the entire lifecycle keeps team members coordinated and offers a mechanism to gauge progress. Large projects with many personnel responsible for making decisions require a formal process and automated support to assist team members in documenting their decisions. Traceability of decisions and documentation rationale is key to understanding the impact of decisions related to modeling, design, implementation, test, and maintenance. The SEPA effort proposes both a methodology and supporting tool suite (leveraging various knowledge representation and reasoning schemes) to facilitate development of object-oriented designs from evolving requirements. SEPA creates traceable, comprehensible, and extensible system design specifications based on requirements from system clients and domain experts. The funnel abstraction is chosen to represent the narrowing, refining, and structuring of user requirements into a system design. User inputs are refined by: (1) merging inputs from multiple sources, (2) distinguishing between inputs relating to system requirements and those relating to general domain knowledge, (3) constructing an object-oriented architecture, (4) mapping requirements to technology solutions, and (5) providing a framework for evaluating system design.

AAAI Conference 1999 Short Paper

A Framework for Problem Solving Activities in Multi-Agent Systems

• D. C. Han
• T. H. Liu
• K. S. Barber
• University of Texas at Austin

The basic research issues in multi-agent systems (MAS) include problem decomposition, task distribution, communication, plan synthesis, coordination, conflict resolution, and organization design. For practical implementation, there is a need for an integrated framework that can help MAS designers to select appropriate techniques for building their specific systems. Difficulties in the integration of techniques for each of these issues is due to the interdependencies among the issues themselves. We propose a framework that describes the activities that occur during problem solving. This framework is based upon the premise that meta-level reasoning about the agents’ activities adds flexibility to each agent, allowing them to adjust to changes in their environments or operating conditions.

AAAI Conference 1999 Short Paper

OBDD-Based Planning with Real-Valued Variables in Non-Deterministic Environments

• A. Goel
• K. S. Barber
• University of Texas at Austin

We are developing a planner that can efficiently handle non-determinism and real variables using neither relative values nor explicit enumeration. In doing so, we are leveraging tools and representations from planning and logic synthesis for computer-aided verification.

AAAI Conference 1999 Conference Paper

Sensible Agents: Demonstration of Dynamic Configuration of Agent Organizations for Responsive Planning Operations

• K. S. Barber
• A. Goel
• D. Han
• J. Kim
• T. H. Liu
• C. E. Martin
• R. McKay
• The University of Texas

Decisions rarely occur in isolation, and decision makers must often respond to dynamic and unexpected events. A decision-maker must consider not only its own possible actions but also the possible behaviors and the resources of others who may either assist with planning and execution, accidentally interfere, or maliciously interfere. Dynamic Adaptive Autonomy (DAA) is the fundamental technology of Sensible Agents that permits a decision-making agent (responsible for planning and execution) to react, adjust, and respond to unpredictable environments. Sensible Agents can (1) assess current and potential interaction styles for planning, and (2) optimize planning frameworks by adjusting these styles. To address these issues, dynamic configuration of decision-making agent organizations is a must. Some specific research that has contributed to flexible, adaptive multi-agent coordination includes partial global planning (Durfee and Lesser, 1987), organizational self-design (Ishida et al., 1992), TEAMS flexible teamwork (Tambe, 1997), RETSINA matchmaking (Sycara and Pannu, 1998), and organizational fluidity (Glance and Huberman, 1993). However, these techniques do not specifically adapt agent planning-interaction styles.