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Found 5 papers, 2 papers with code
Preference-Based Monte Carlo Tree Search
To deal with such cases, the experimenter has to supply an additional numeric feedback signal in the form of a heuristic, which intrinsically guides the agent.
Ordinal Monte Carlo Tree Search
In many problem settings, most notably in game playing, an agent receives a possibly delayed reward for its actions.
Deep Ordinal Reinforcement Learning
Reinforcement learning usually makes use of numerical rewards, which have nice properties but also come with drawbacks and difficulties.
Ordinal Bucketing for Game Trees using Dynamic Quantile Approximation
In this paper, we present a simple and cheap ordinal bucketing algorithm that approximately generates $q$-quantiles from an incremental data stream.
Ordinal Monte Carlo Tree Search
In this paper we take a look at MCTS, a popular algorithm to solve MDPs, highlight a reoccurring problem concerning its use of rewards, and show that an ordinal treatment of the rewards overcomes this problem.
