6 citations · 10 across the 3 of their papers we have counts for
5 papers
Ordinal Monte Carlo Tree Search
Tobias Joppen, Johannes Fürnkranz
In many problem settings, most notably in game playing, an agent receives a possibly delayed reward for its actions. Often, those rewards are handcrafted and not naturally given. E…
Ordinal Bucketing for Game Trees using Dynamic Quantile Approximation
Tobias Joppen, Tilman Strübig, Johannes Fürnkranz
In this paper, we present a simple and cheap ordinal bucketing algorithm that approximately generates -quantiles from an incremental data stream. The bucketing is done dynamical…
Deep Ordinal Reinforcement Learning
Alexander Zap, Tobias Joppen, Johannes Fürnkranz
Reinforcement learning usually makes use of numerical rewards, which have nice properties but also come with drawbacks and difficulties. Using rewards on an ordinal scale (ordinal…
Ordinal Monte Carlo Tree Search
Tobias Joppen, Johannes Fürnkranz
In many problem settings, most notably in game playing, an agent receives a possibly delayed reward for its actions. Often, those rewards are handcrafted and not naturally given. E…
Preference-Based Monte Carlo Tree Search
Tobias Joppen, Christian Wirth, Johannes Fürnkranz
Monte Carlo tree search (MCTS) is a popular choice for solving sequential anytime problems. However, it depends on a numeric feedback signal, which can be difficult to define. Real…