HyperNEAT, a generative encoding for evolving artificial neural networks (ANNs), has the unique and powerful ability to exploit the geometry of a problem (e.g., symmetries) by enc...
In this paper we propose the use of small global memory for a viewer’s immediate surroundings to assist in recognising places that have been visited previously. We call this glob...
The underlying research topics and the architecture of the UBU team are briefly described. The aim of developing UBU is to subject a series of tools and procedures for agent decis...
We contribute an approach for interactive policy learning through expert demonstration that allows an agent to actively request and effectively represent demonstration examples. I...
In this paper, we outline a framework for the development of natural language interfaces to agent systems with a focus on action representation. The architecture comprises a natur...