YAML Metadata Warning:The task_ids "emoji_quest_rl" is not in the official list: acceptability-classification, entity-linking-classification, fact-checking, intent-classification, language-identification, multi-class-classification, multi-label-classification, multi-input-text-classification, natural-language-inference, semantic-similarity-classification, sentiment-classification, topic-classification, semantic-similarity-scoring, sentiment-scoring, sentiment-analysis, hate-speech-detection, text-scoring, named-entity-recognition, part-of-speech, parsing, lemmatization, word-sense-disambiguation, coreference-resolution, extractive-qa, open-domain-qa, closed-domain-qa, news-articles-summarization, news-articles-headline-generation, dialogue-modeling, dialogue-generation, conversational, language-modeling, text-simplification, explanation-generation, abstractive-qa, open-domain-abstractive-qa, closed-domain-qa, open-book-qa, closed-book-qa, text2text-generation, slot-filling, masked-language-modeling, keyword-spotting, speaker-identification, audio-intent-classification, audio-emotion-recognition, audio-language-identification, multi-label-image-classification, multi-class-image-classification, face-detection, vehicle-detection, instance-segmentation, semantic-segmentation, panoptic-segmentation, image-captioning, image-inpainting, image-colorization, super-resolution, grasping, task-planning, tabular-multi-class-classification, tabular-multi-label-classification, tabular-single-column-regression, rdf-to-text, multiple-choice-qa, multiple-choice-coreference-resolution, document-retrieval, utterance-retrieval, entity-linking-retrieval, fact-checking-retrieval, univariate-time-series-forecasting, multivariate-time-series-forecasting, visual-question-answering, document-question-answering, pose-estimation

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\_   _____/ _____   ____    |__|__| \_____  \  __ __   ____   _______/  |_ 
 |    __)_ /     \ /  _ \   |  |  |  /  / \  \|  |  \_/ __ \ /  ___/\   __\
 |        \  Y Y  (  <_> )  |  |  | /   \_/.  \  |  /\  ___/ \___ \  |  |  
/_______  /__|_|  /\____/\__|  |__| \_____\ \_/____/  \___  >____  > |__|  
        \/      \/      \______|           \__>           \/     \/

Emoji Quest RL Dataset

This was created as a Reinforcement learning dataset from Emoji Quest RL gameplay. It features a Single human playthrough of Emoji Quest RL — turn-based RPG with combat, stat upgrades, resting & crafting. The game is available for download in the /gym/ folder of the repo so players can create their own datasets.

It contains 85 decision points / states → full session: lvl 1→8, 13 enemies defeated, 1451 gold earned, ~169s playtime. Two splits / files (Parquet + CSV):

game_states — snapshots at every decision point (default)
decisions — focused on player choices + immediate results

Key Columns:

timestamp — event time
action — what happened (e.g. "Spell", "enemy_attack", "upgrade_int", "inn_rest", "craft_armor_1")
reward — shaped signal (-100..500): + for damage/victory/progression, - for taken damage
outcome — result type (damage_dealt, damage_taken, victory, progression, etc.)
decision_type — category (Spell, enemy_attack, upgrade_stat, rest_inn, craft_armor)
player_state / player_state_snapshot — JSON: level, hp/mp, str/int/vit/def, gold, skillPoints, exp, equipment flags
enemy_info / enemy_state — JSON: emoji enemy name (💾 Datavore etc.), hp, attack, boss/eliteness
enemy_count — 1–13
game_state — always "playing"

game_states.csv

Game state snapshots at each decision point. Contains player and enemy stats.

decisions.csv

Player decisions with rewards and outcomes. Contains action choices and results.

Summary

Total states: 85
Total decisions: 85
Total enemies defeated: 13
Total gold earned: 1451
Total XP earned: 121
Play time: 169 seconds
Final level: 8
Final gold: 1451
Final HP: 210
Final MP: 20

Downloads last month: 35

Total file size:

328 kB