Multi-Agent Programming Contest Research Articles

The USP Farmers herding team

This paper describes the development steps and core ideas used by the USP Farmers herding team, that has participated in the 2010 edition of the Multi-Agent Programming Contest (MAPC 2010). This is the third year that the competitors must design a team of herding agents, whose global goal is to lead a maximum number of cows to their own corral. As this is a very complex task and requires coordination of the team, we have developed the individual agents using the Jason (Bordini et al. 2007) interpreter for AgentSpeak(L) (Rao 1996). Moreover, the coordination strategy was defined using the $\mathcal{M}$ OISE ?+? (Hubner et al. 2002, 2007) organizational model. We have also used the idea of artifact (Ricci et al. 2007) to develop global services, available to all the agents. Moreover, it is clear that for this contest some pure procedural processing should be developed in a lower abstraction level (Hubner et al. 2008); therefore some calculation and pre-defined global decisions were implemented by Java classes.

Galoan: a multi-agent approach to herd cows

This paper describes the team Galoan (it is a local Persian name that means shepherd), one of the participants in the Multi-Agent Programming Contest 2010. We present the agents' architecture as well as the team strategies and the coordination and cooperation approaches. Our system was developed using the blackboard style and was implemented in Java. In our approach each agent stores its perception in a shared world model which is called blackboard. Coordination has been implemented through a supervisor. The supervisor uses the stored information in the blackboard and coordinates the agents to achieve a goal. Finally, we outline our observations and discuss the performance of our team.

Improving multi-agent systems using Jason

We describe the approach used to develop the multi-agent system of herders that competed as the Jason-DTU team at the Multi-Agent Programming Contest 2010. We also participated in 2009 with a system developed in the agent-oriented programming language Jason which is an extension of AgentSpeak. We used the implementation from 2009 as a foundation and therefore much of the work done this year was on improving that implementation. We present a description which includes design and analysis of the system as well as the main features of our agent team strategy. In addition we discuss the technologies used to develop this system as well as our future goals in the area.

Argonauts: a working system for motivated cooperative agents

This paper presents the Argonauts multi-agent framework which was developed as part of a one year student project at Technische Universitat Dortmund. The Argonauts framework builds on a BDI approach to model rational agents that act cooperatively in a dynamic and indeterministically changing environment. However, our agent model extends the traditional BDI approach in several aspects, most notably by incorporating motivation into the agent's goal selection mechanism. The framework has been applied by the Argonauts team in the 2010 version of the annual multi-agent programming contest organized by Technische Universitat Clausthal. In this paper, we present a high-level specification and analysis of the actual system used for solving the given scenario. We do this by applying the GAIA methodology, a high-level and iterative approach to model communication and roles in multi-agent scenarios. We further describe the technical details and insights gained during our participation in the multi-agent programming contest.

The multi-agent programming contest from 2005–2010

The Multi-Agent Programming Contest is an annual international event on programming multi-agent systems: Teams of agents participate in a simulated cooperative scenario. It started in 2005 and is organised in 2010 for the sixth time. The contest is an attempt to stimulate research in the area of multi-agent system development and programming by (i) identifying key problems in the field and (ii) collecting suitable benchmarks that can serve as milestones for testing multi-agent programming languages, platforms and tools. This article provides a short history of the contest since it started and reports in more detail on the cows and cowboys scenario implemented for the 2008, 2009 and 2010 contest editions. We briefly discuss the underlying technological background and conclude with a critical discussion of the experiences and lessons learned.

A BDI agent system for the cow herding domain

We describe the current state of our multi-agent system for agents playing games in grid-like domains. The framework follows the BDI model of agency and is used as the main project for a seminar course on agent-oriented programming and design. When it comes to design, the Prometheus methodology has been used by relying on the Prometheus design tool (PDT) that supports the methodology. In terms of programming language, we have used the JACK agent platform. We believe the domains developed as part of the Multi-Agent Programming Contest are the right type of settings for evaluating our research, in that it provides enough complexity to explore various aspects of multi-agent development while being sufficiently bounded to make the development effort worthwhile.

Building multi-agent systems using Jason

We provide a detailed description of the Jason-DTU system, including the used methodology, tools as well as team strategy. We also discuss the experience gathered in the contest. In spring 2009 the course "Artificial Intelligence and Multi-Agent Systems" was held for the first time on the Technical University of Denmark (DTU). A part of this course was a short introduction to the multi-agent framework Jason, which is an interpreter for AgentSpeak, an agent-oriented programming language. As the final project in this course a solution to the Multi-Agent Programming Contest from 2007, the Gold Miners scenario, was implemented. Finally we decided to participate in this year's contest with an implementation made in Jason as well.

Using agent- and organisation-oriented programming to develop a team of agents for a competitive game

The multi-agent programming contest uses a cow-herding scenario where two teams of cooperative agents compete for resources against each other. We developed such a team of agents using two well-known platforms, one based on a logic-based agent-oriented programming language, called Jason, and the other based on an organisational model, called $\mathcal{M}$ oise. While there is significant research on both agent programming and agent organisations, this was one of the first applications of a combined approach where we can program deliberative agents and organise them using a sophisticated organisational model. In this paper, we describe and discuss our contribution to the multi-agent contest using this combination of agent and organisation programming.

MOO—MicroJIAC agents operating oxen

The MicroJIAC team has participated in the Multi-Agent Programming Contest 2007 with some success. This year, we attended again. Our contest contribution was implemented by a student during a university course using the current version of our agent framework. Unlike the gold mining scenario of MAPC 2007, this year's cow herding scenario had higher complexity and was a very good testbed to evaluate our new agent framework.