Michael Köster

The Multi-Agent Programming Contest

The international Multi-Agent Programming Contest (MAPC), is a community-serving effort to facilitate advances in programming multiagent systems (MAS) by (1) developing benchmark problems, (2) enabling head-to-head comparison of MAS’s and (3) supporting educational efforts in the design and implementation of MAS’s. The tournament platform, MASSim, is freely available and we encourage everybody to download it and use it in the classroom

The multi-agent programming contest 2011: a résumé

The Multi-Agent Programming Contest is an annual AI competition aiming at comparing deliberative techniques for problem solving, that are based on formal approaches and computational logics. In 2011 the Contest was held for the seventh time and witnessed the introduction of the new agents on Mars scenario. We give an overview of the Contest in general but concentrate on the agents on Mars scenario. We also provide empirical results that we received before, during and after the tournament.

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 Scalable Runtime Platform for Multiagent-Based Simulation

Using purely agent-based platforms for any kind of simulation requires to address the following challenges: (1) scalability (efficient scheduling of agent cycles is difficult), (2) efficient memory management (when and which data should be fetched, cached, or written to/from disk), and (3) modelling (no generally accepted meta-models exist: what are essential concepts, what just implementation details?). While dedicated professional simulation tools usually provide rich domain libraries and advanced visualisation techniques, and support the simulation of large scenarios, they do not allow for “agentization” of single components. We are trying to bridge this gap by developing a distributed, scalable runtime platform for multiagent simulation, MASeRaTi, addressing the three problems mentioned above. It allows to plug-in both dedicated simulation tools (for the macro view) as well as the agentization of certain components of the system (to allow a micro view). If no agent-related features are used, its performance should be as close as possible to the legacy system used.

Abstraction for model checking modular interpreted systems over ATL

We present an abstraction technique for model checking multi-agent systems given as modular interpreted systems (

Two Case Studies for Jazzyk BSM

\textsc{MIS}

The Multi-Agent Programming Contest 2012

) (introduced by Jamroga and Agotnes).

Multi-Agent Programming Contest 2013

\textsc{MIS}

Multi-Agent Programming Contest 2013: The Teams and the Design of Their Systems

allow for succinct representations of compositional systems, they permit agents to be removed, added or replaced and they are modular by facilitating control over the amount of interaction. Specifications are given as arbitrary

A Game Theoretic Approach for Optimal Network Topologies in Opportunistic Networks

\textsc{ATL}