Partially Observable Markov Decision Processes (POMDPs) provide a rich framework for sequential decision-making under uncertainty in stochastic domains. However, solving a POMDP i...
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Many conceptual studies of local cortical networks assume completely random wiring. For spatially extended networks, however, such random graph models are inadequate. The geometry...
Symmetric net structure yields symmetric net behaviour. Thus, knowing the symmetries of a net, redundant calculations can be skipped. We present a framework for the calculation of ...
— Reinforcement learning (RL) is one of the most general approaches to learning control. Its applicability to complex motor systems, however, has been largely impossible so far d...