Les Agents comme des interpr\'eteurs Scheme : Sp\'ecification dynamique par la communication

TL;DR

This paper discusses an extension of the STROBE model where Agents act as Scheme interpreters capable of evolving their knowledge through conversation, enabling dynamic problem specification and service generation, especially useful in grid computing.

Contribution

It introduces a dynamic, conversation-based approach for Agents as interpreters with learning capabilities, extending prior models to support evolving specifications.

Findings

Demonstrates dynamic service generation using nondeterministic interpreters.

Shows how Agents can refine specifications through dialogue.

Illustrates potential applications beyond grid computing.

Abstract

We proposed in previous papers an extension and an implementation of the STROBE model, which regards the Agents as Scheme interpreters. These Agents are able to interpret messages in a dedicated environment including an interpreter that learns from the current conversation therefore representing evolving meta-level Agent's knowledge. When the Agent's interpreter is a nondeterministic one, the dialogues may consist of subsequent refinements of specifications in the form of constraint sets. The paper presents a worked out example of dynamic service generation - such as necessary on Grids - by exploiting STROBE Agents equipped with a nondeterministic interpreter. It shows how enabling dynamic specification of a problem. Then it illustrates how these principles could be effective for other applications. Details of the implementation are not provided here, but are available.