AAMAS conference in London and research paper presentation

An important challenge in the field of autonomous open-ended learning is the autonomous learning of interdependent tasks, and in particular when such interdependencies are non-stationary, so that the robot has to modify the acquired knowledge to properly sequence goals that constitute preconditions for other ones. The research paper proposes a hierarchical robotic architecture to address these types of scenarios, allowing for the autonomous learning of both the skills necessary to achieve the multiple goals, and of the sequences reflecting the relations between them. 

AAMAS is the largest and most influential conference in the area of agents and multiagent systems, bringing together researchers and practitioners in all areas of agent technology and providing and internationally renowned high-profile forum for publishing and finding out about the latest developments in the field.