Artificial Intelligence
User Stories Applied: For Agile Software Development
User Stories Applied: For Agile Software Development
Extreme Programming Explained: Embrace Change (2nd Edition)
Extreme Programming Explained: Embrace Change (2nd Edition)
Analysis of Dynamic Task Allocation in Multi-Robot Systems
International Journal of Robotics Research
Unit testing in multi-agent systems using mock agents and aspects
Proceedings of the 2006 international workshop on Software engineering for large-scale multi-agent systems
SoSAA: a framework for integrating components & agents
Proceedings of the 2009 ACM symposium on Applied Computing
Debugging agents in agent factory
ProMAS'06 Proceedings of the 4th international conference on Programming multi-agent systems
CArtAgO: a framework for prototyping artifact-based environments in MAS
E4MAS'06 Proceedings of the 3rd international conference on Environments for multi-agent systems III
AF-APL – bridging principles and practice in agent oriented languages
ProMAS'04 Proceedings of the Second international conference on Programming Multi-Agent Systems
Dynamic Assignment in Distributed Motion Planning With Local Coordination
IEEE Transactions on Robotics
The multi-agent programming contest from 2005---2010
Annals of Mathematics and Artificial Intelligence
From bogtrotting to herding: a UCD perspective
Annals of Mathematics and Artificial Intelligence
ProMAS'11 Proceedings of the 9th international conference on Programming Multi-Agent Systems
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This is the second year in which a team from University College Dublin has participated in the Multi Agent Contest ( http://www.multiagentcontest.org/2009 ). This paper describes the system that was created to participate in the contest, along with observations of the team's experiences in the contest. The system itself was built using the AFAPL agent programming language running on the Agent Factory platform. A hybrid control architecture inspired by the SoSAA strategy aided in the separation of concerns between low-level behaviours (such as movement and obstacle evasion) and higher-level planning and strategy.