The goal in automatic programming is to get a computer to perform a task by telling it what needs to be done, rather than by explicitly programming it. This paper considers the ta...
We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...
Agents in dynamic environments have to deal with world rep- To appear in: RoboCup 2005: Robot Soccer World Cup IX, c Springer-Verlag, 2006 resentations that change over time. In or...
Andreas D. Lattner, Andrea Miene, Ubbo Visser, Ott...
How to achieve shared meaning is a significant issue when more than one intelligent agent is involved in the same domain. We define the task of concept convergence, by which intell...
My research attempts to address on-line action selection in reinforcement learning from a Bayesian perspective. The idea is to develop more effective action selection techniques b...