Improving Search with Supervised Learning in Trick-Based Card Games
Authors: Christopher Solinas, Douglas Rebstock, Michael Buro1158-1165
AAAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | 4 Experiments We use two methods of measuring inference performance in this work. First, we measure the quality of our inference technique in isolation using a novel metric. Second, we show the effect of using inference in a card player by running tournaments against several baseline players. |
| Researcher Affiliation | Academia | Christopher Solinas, Douglas Rebstock, Michael Buro Department of Computing Science, University of Alberta Edmonton, Canada {solinas,drebstoc,mburo}@ualberta.ca |
| Pseudocode | Yes | Algorithm 1: PIMC with state inference |
| Open Source Code | No | The paper does not include an unambiguous statement that the authors are releasing their source code for the described methodology, nor does it provide a direct link to a code repository. |
| Open Datasets | Yes | The networks are trained using a total of 20 million games played by humans on a popular Skat server (DOSKV 2018). |
| Dataset Splits | No | The paper mentions using a 'validation set' for early stopping but does not provide specific dataset split information (exact percentages, sample counts, or detailed splitting methodology). |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types, or memory amounts) used for running its experiments, only vague terms like 'modern hardware'. |
| Software Dependencies | No | The paper mentions using 'Python Tensorflow (Abadi et al. 2016)' but does not provide specific version numbers for these software components. |
| Experiment Setup | Yes | Table 1 lists all hyperparameters used during training. Parameter Value Dropout 0.8 Batch Size 32 Optimizer ADAM Learning Rate (LR) 10^-4 LR Exponential Decay 0.96 / 10,000,000 batches |