text-based games

Jericho is a learning environment for man-made Interactive Fiction (IF) games. Source: Interactive Fiction Games: A Colossal Adventure

A dataset of games played in the card game "Cards Against Humanity" (CAH), by human players, derived from the online CAH labs. Each round includes the cards presented to users - a "black" prompt with a blank or question and 10 "white" punchlines as possible responses, and which punchline was picked by a player each round, along with text and metadata. An example prompt is “TSA guidelines now prohibit ___ on airplanes”. Candidate punchlines are “Goblins”, “BATMAN!!!”, “Poor people”, and “The right amount of cocaine”. Importantly, many cards are offensive or politically incorrect. Used to explore human humor preferences. Available upon request from CAH labs: mail@cardsagainsthumanity.com Train/test splits and data processing available in the paper/code: "Cards Against AI: Predicting Humor in a Fill-in-the-blank Party Game": https://github.com/ddofer/CAH

To evaluate our proposed strategy of asynchronous communication for LLMs, we run games of Mafia with human players, incorporating an LLM-based agent as an additional player, within an asynchronous chat environment. The data includes all players messages and votes including timestamps, game management messages (e.g., announcements of the beginning and end of phases), in addition to records related to the agent, such as the prompts that were provided at each timestamp. While prior datasets for Mafia exist, ours is the first to integrate an LLM agent, allowing analysis of human-LLM interactions. Detailed analysis of the data is available in our paper: Time to Talk: LLM Agents for Asynchronous Group Communication in Mafia Games

TextWorld KG is a dynamic Knowledge Graph (KG) extraction dataset. It is based on a set of text-based games generated using. That framework allows to extract the underlying partial KG for every state, i.e., the subgraph that represents the agent’s partial knowledge of the world – what it has observed so far. All games share the same overarching theme: the agent finds itself hungry in a simple modern house with the goal of gathering ingredients and cooking a meal. Source: https://arxiv.org/abs/1910.09532