This paper describes a computationally feasible approximation to the AIXI agent, a universal reinforcement learning agent for arbitrary environments. AIXI is scaled down in two ke...
Joel Veness, Kee Siong Ng, Marcus Hutter, William ...
We present a class of graphical models for directly representing the joint cumulative distribution function (CDF) of many random variables, called cumulative distribution networks...
This paper describes a completely implemented, fully autonomous software system for soccer playing quadruped robots. The system includes real-time color vision, probabilistic loca...
This report outlines the use of a relational representation in a Multi-Agent domain to model the behaviour of the whole system. A desired property in this systems is the ability of...
This paper presents a framework for describing the spatial distribution and the global frequency of agents who play the spatial prisoner’s dilemma with coalition formation. The ...