We consider here the problem of building a never-ending language learner; that is, an intelligent computer agent that runs forever and that each day must (1) extract, or read, inf...
Andrew Carlson, Justin Betteridge, Bryan Kisiel, B...
This paper introduces a principled approach for the design of a scalable general reinforcement learning agent. This approach is based on a direct approximation of AIXI, a Bayesian...
Joel Veness, Kee Siong Ng, Marcus Hutter, David Si...
Software developers increasingly rely on information from the Web, such as documents or code examples on Application Programming Interfaces (APIs), to facilitate their development...
Jinhan Kim, Sanghoon Lee, Seung-won Hwang, Sunghun...
We present a novel method to control a biped humanoid robot to walk on unknown inclined terrains, using an online learning algorithm to estimate in real-time the local terrain fro...
Trial-based approaches offer an efficient way to solve singleagent MDPs and POMDPs. These approaches allow agents to focus their computations on regions of the environment they en...