Interactive Fiction Games: A Colossal Adventure
Authors: Matthew Hausknecht, Prithviraj Ammanabrolu, Marc-Alexandre Côté, Xingdi Yuan7903-7910
AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We evaluate the agents across a set of thirty-two Jericho-supported games with the aims of 1) showing the feasibility of reinforcement learning on a variety of different IF games, 2) creating a reproducible benchmark for future work, 3) investigating the difference between choice-based and template-based action spaces, and 4) comparing performance of general IF game playing agents (NAIL), single-game agents (DRRN and TDQN), and a random agent (RAND) which uniformly sample commands from a set of canonical actions. |
| Researcher Affiliation | Collaboration | Matthew Hausknecht Microsoft Research AI Prithviraj Ammanabrolu Georgia Institute of Technology Marc-Alexandre Cˆot e Microsoft Research Montr eal Xingdi Yuan Microsoft Research Montr eal |
| Pseudocode | Yes | Algorithm 1 Procedure for Identifying Valid Actions |
| Open Source Code | Yes | Jericho is available at https://github.com/microsoft/jericho. |
| Open Datasets | Yes | Jericho supports a set of fifty-six human-made IF games that cover a variety of genres... There exists a large collection of over a thousand unsupported games 3, which may be useful for unsupervised pretraining or intrinsic motivation. 3https://github.com/BYU-PCCL/z-machine-games |
| Dataset Splits | No | The paper mentions 'Additional experiment details and hyperparameters are located in the supplementary material' but does not provide specific train/validation/test dataset splits (e.g., percentages, sample counts, or explicit splitting methodology) in the main text. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU models, CPU types, or memory) used for running the experiments. |
| Software Dependencies | No | The paper mentions software components like 'Python-based IF environment', 'Sentence Piece model', and 'GRU encoders' but does not provide specific version numbers for these or other software dependencies. |
| Experiment Setup | No | The paper states 'Additional experiment details and hyperparameters are located in the supplementary material' but does not include specific experimental setup details (e.g., concrete hyperparameter values, training configurations, or system-level settings) within the main text. |