Foundational Underpinnings for Pragmatic Agent-based Systems

Marcin Paprzycki, Niranjan Suri

Abstract


Foundational Underpinnings for Pragmatic Agent-based Systems

This issue is the second of a two issue collection of selected papers from the AIMS (Agents, Interactions, Mobility, and Systems) conference track. AIMS began in 2002 as part of the ACM SAC (Symposium on Applied Computing) and continued for five years. The first conference was held in Madrid (Spain). Subsequent conferences were held in Melbourne (Florida, USA), Nicosia (Cyprus), Santa Fe (New Mexico, USA), and Dijon (France). The track was primarily created to provide a venue for applied topics in software agents, but became the only venue for papers on mobile agents, as the IEEE conference on Mobile Agents was discontinued after 2002. The first issue focused on papers related to mobile agents. This second issue focuses on software agents and contains eight papers.

In the first paper, Alberti and colleagues address the problem of verifying agent interaction protocols that dictate how agents communicate with each other in a multi-agent system. They propose a system based on Prolog that enforces Social Integrity Constraints—that govern how agents interact with other agents. They also apply their approach to the standard FIPA Contract-Net protocol.

In the second paper, Meneguzzi, Zorzo, Costa Móra, and Luck discuss how to incorporate planning into the Belief, Desires, Intentions (BDI) model based agent systems. Their approach attempts to supplement the BDI model with a planning approach in order to provide efficient means-end reasoning. A hybrid system with a blend of programming platforms integrates reasoning and graphplan generation. This integration addresses the long awaited requirement for BDI pragmatism and provides a novel technological framework.

The third paper by Albayrak, Wollny, Lommatzsch, and Milosevic describes an application of agent technology to information filtering. Their system uses information agents to retrieve content from a number of diverse sources including the web. This information is then filtered for individual users via personal agents, based on the user profiles. They also describe their implementation to support browsing information via PDAs and cellphones.

In the fourth paper, Hexmoor and Mclaughlan address the issue of adjustable autonomy in the context of the Personal Satellite Assistant (PSA)—a softball sized flying robot onboard the space station. The authors propose a computational approach to adjustable autonomy, which considers the tradeoffs between human intervention and guidance to an agent versus the agent's own autonomous behavior.

The fifth paper by Peña and colleagues address the problem of protocol design for multi-agent systems. Unlike the logic-based approach adopted by the first paper, this approach proposes a top-down mechanism for designing the protocols. They model the protocols with FSAs that are successively refined until they are reduced to simple message sequences.

In the sixth paper, Zhang proposes an approach to proactive communication to improve performance of multi-agent teamwork. The goal is to allow agents cooperating in a team to anticipate each other's information needs in a proactive manner and to communicate the information to other agents.

In the seventh paper, Lomonosov and Sitharam discuss the tradeoff between stability, optimality, and complexity for network games. Their approach is based on the Nash equilibrium, with stability being defined as the ability to reach a Nash equilibrium and optimality being defined as the distance between to the equilibrium solution and an optimal solution.

The paper by Carlsson and Jönsson discusses cooperative strategies and their application to the iterated prisoner's dilemma and the chicken game.

Decision support systems for resource management in the corporate world require sophisticated administration and management. Multiagent systems approach to this topic is the tenet of the paper by Symeonidis, et. al., in this issue. Customer management as well as resource tracking and recommendation are core issued discussed.

Marcin Paprzycki,
Niranjan Suri.


References



Refbacks

  • There are currently no refbacks.