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...
Techniques for computation on generalized diagrams are defined and the KM implications are explored. Descriptive Computing is presented and plan computation based on world models t...
We present a general framework for defining nonmonotonic systems based on the notion of preferred maximal consistent subsets of the premises. This framework subsumes David Poole...
There exist many tools for capturing imprecision in probabilistic representations. Among them are random sets, possibility distributions, probability intervals, and the more recen...
Recent results have used game theory to explore the nature of optimal investments in the security of simple series and parallel systems. However, it is clearly important in practi...