Publication
This paper introduces a simple, general framework for likelihood-free Bayesian reinforcement learning, through Approximate Bayesian Computation (ABC). The main advantage is th...
Publication
This paper proposes a simple linear Bayesian approach to reinforcement learning. We show that
with an appropriate basis, a Bayesian linear Gaussian model is sufficient for accurat...
INFOCOM
2012
IEEE
12 years 10 months ago
2012
IEEE
We derive bounds on the expected loss for authentication protocols in channels which are constrained due to noisy
conditions and communication costs. This is motivated by a
numbe...
Publication
We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or ...
Publication
In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinfo...