This paper proposes the incremental Bayesian optimization algorithm (iBOA), which modifies standard BOA by removing the population of solutions and using incremental updates of t...
This work presents a lookahead-based exploration strategy for a model-based learning agent that enables exploration of the opponent's behavior during interaction in a multi-a...
Designing controllers for modular robots is difficult due to the distributed and dynamic nature of the robots. In this paper fractal gene regulatory networks are evolved to control...
Payam Zahadat, David Johan Christensen, Ulrik Pagh...
A new algorithm for learning one-variable pattern languages is proposed and analyzed with respect to its average-case behavior. We consider the total learning time that takes into...
We describe a nonparametric Bayesian approach to generalizing from few labeled examples, guided by a larger set of unlabeled objects and the assumption of a latent tree-structure ...
Charles Kemp, Thomas L. Griffiths, Sean Stromsten,...