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Tobias Joppen

5 papers hereh-index 342 citations9 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4
  • middle author1

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.AI4
  • cs.LG1

identity via Semantic Scholar / OpenAlex

activity
20182021
most citedDeep Ordinal Reinforcement Learning

6 citations · 10 across the 3 of their papers we have counts for

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2021

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…

cs.AI2019★ 1 cited

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 q-quantiles from an incremental data stream. The bucketing is done dynamical…

cs.AI2019

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…

cs.AI2018★ 3 cited

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…

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