REVIEW 3 cited by
Interactive Fiction Games: A Colossal Adventure
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
A hallmark of human intelligence is the ability to understand and communicate with language. Interactive Fiction games are fully text-based simulation environments where a player issues text commands to effect change in the environment and progress through the story. We argue that IF games are an excellent testbed for studying language-based autonomous agents. In particular, IF games combine challenges of combinatorial action spaces, language understanding, and commonsense reasoning. To facilitate rapid development of language-based agents, we introduce Jericho, a learning environment for man-made IF games and conduct a comprehensive study of text-agents across a rich set of games, highlighting directions in which agents can improve.
Forward citations
Cited by 3 Pith papers
-
Derivation and Numerical Simulation of a Thermodynamically Consistent Magneto Two-Phase Flow Model for Magnetic Drug Targeting
Leading omni-modal AI models show superhuman memory but brittle cross-modal fusion: conflicting or redundant sensory input degrades performance, and removing a modality can sometimes improve it.
-
TextQuests: How Good are LLMs at Text-Based Video Games?
Frontier LLMs complete few of 25 Infocom text adventures even when given the official hint booklets, revealing a weakness in sustained long-context reasoning.
-
Constructing coherent spatial memory in LLM agents through graph rectification
LLM-MapRepair uses versioned graph history and an edge-impact score to detect and repair structural errors in incrementally built LLM navigation graphs, improving repair accuracy from ~6% to ~55% on cleaned MANGO games.
Discussion (0). Continue with ORCID to comment.