Augmenting Agent Platforms to Facilitate Conversation Reasoning

Within Multi Agent Systems, communication by means of Agent Communication Languages (ACLs) has a key role to play in the co-operation, co-ordination and knowledge-sharing between agents. Despite this, complex reasoning about agent messaging, and specifically about conversations between agents, tends not to have widespread support amongst general-purpose agent programming languages. ACRE (Agent Communication Reasoning Engine) aims to complement the existing logical reasoning capabilities of agent programming languages with the capability of reasoning about complex interaction protocols in order to facilitate conversations between agents. This paper outlines the aims of the ACRE project and gives details of the functioning of a prototype implementation within the Agent Factory multi agent framework

A process model for the design of multi-agent systems

In this paper, we propose a pragmatic process model for the development of multi-agent system based on the combination of standard software engineering techniques with a special focus on multi-agent systems. The resulting process model is the attempt to make our experience in the design of multi-agent systems available to other system designers. The approach presented in this paper has evolved over several years and it has been successfully applied and refined in different types of multi-agent systems. A short case study of our latest project is included in the paper

OptiMUS: Scalable Optimization Modeling with (MI)LP Solvers and Large Language Models

Optimization problems are pervasive in sectors from manufacturing and distribution to healthcare. However, most such problems are still solved heuristically by hand rather than optimally by state-of-the-art solvers because the expertise required to formulate and solve these problems limits the widespread adoption of optimization tools and techniques. This paper introduces OptiMUS, a Large Language Model (LLM)-based agent designed to formulate and solve (mixed integer) linear programming problems from their natural language descriptions. OptiMUS can develop mathematical models, write and debug solver code, evaluate the generated solutions, and improve its model and code based on these evaluations. OptiMUS utilizes a modular structure to process problems, allowing it to handle problems with long descriptions and complex data without long prompts. Experiments demonstrate that OptiMUS outperforms existing state-of-the-art methods on easy datasets by more than $20\%$ and on hard datasets (including a new dataset, NLP4LP, released with this paper that features long and complex problems) by more than $30\%$

Wake up and Smell the Ginseng: International Trade and the Rise of Incremental Innovation in Low-Wage Countries

Increasingly, a small number of lowwage countries such as China, India and Mexico are involved in incremental innovation. That is, they are responsible for resolving productionline bugs and suggesting product improvements. We provide evidence of this new phenomenon and develop a model in which there is a transition from oldstyle productcycle trade to trade involving incremental innovation in lowwage countries. The model explains why levels of involvement in incremental innovation vary across lowwage countries and across firms within each lowwage country. We draw out implications for sectoral earnings, living standards, the capital account and, foremost, international trade in goods.international trade, lowwage country innovation

Mobile Agents for Mobile Tourists: A User Evaluation of Gulliver's Genie

How mobile computing applications and services may be best designed, implemented and deployed remains the subject of much research. One alternative approach to developing software for mobile users that is receiving increasing attention from the research community is that of one based on intelligent agents. Recent advances in mobile computing technology have made such an approach feasible. We present an overview of the design and implementation of an archetypical mobile computing application, namely that of an electronic tourist guide. This guide is unique in that it comprises a suite of intelligent agents that conform to the strong intentional stance. However, the focus of this paper is primarily concerned with the results of detailed user evaluations conducted on this system. Within the literature, comprehensive evaluations of mobile context-sensitive systems are sparse and therefore, this paper seeks, in part, to address this deficiency