| dc.description.abstract | In this thesis my final Msc research project in Cognitive Artificial Intelligence is presented. The main issue adressed in this work is the problem of `ad hoc coordination'. Coordination in this context mainly is cooperation in teamwork: interaction between multiple agents that share a certain environment or system, whilst trying to achieve certain goals or objectives together.
When coordination is `ad hoc', an agent does not know what to expect of the other agents and their plans, but nevertheless has to contribute to their teamwork in achieving goals. In this project, the domain of robot soccer is taken as a specific application of the problem of ad hoc coordination, with special attention to the coach robot. The contribution of this work to the problem is twofold: from an agent theory point of view, a formal framework for the robot soccer society of the RoboCup Standard Platform League is designed using the OperA methodology for agent organizations. This framework is grounded in a combination of deontic and temporal logics and provides structures for coordination while still being flexible and allowing for extension with various agent architectures and other lower level implementations. In order to ground the concepts used in the framework, a sensor data-driven module is developed to infer an agent's plans. In order to be able to coordinate ad hoc, the coach first has to learn the ways and plans of his teammates and/or opponents, before deciding on how to adapt his strategy in order to improve the team's performance.
In collaboration with the University of Edinburgh's Robust Autonomy and Decisions robotics group, a plan recognition module has been developed. As an extension of the current methodology towards a more high-level approach of multi-agent interaction, the domain is approached from a logical, multi-agent theory point of view, aiming at structured coordination and teamwork. This thesis yields a thorough agent organization model of the robot soccer society combined with a plan recognition module and suggestions on their connection. | |
