Domain-Independent Game Abstraction using Word Embedding Techniques
The paper presents a domain-independent approach to game abstraction using word embedding techniques. This method allows for the representation of game actions as real-valued vectors, facilitating the abstraction process. Experimental results indicate that while effective, this technique does not surpass specialized algorithms designed for specific games.
- ▪The proposed approach uses word embedding techniques from natural language processing for game abstraction.
- ▪Actions are treated as words, and gameplay data is considered a corpus for training word vectors.
- ▪Experimental results show that the technique is effective but does not outperform specialized algorithms.
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| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.15543 |
| Publication time | Mon, 18 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-18T04:04:54.418Z |
| Last seen | 2026-05-18T04:04:54.418Z |
| Headline source | Publisher (no WeSearch rewrite) |
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| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | 3K1K7jaIDxLd |
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| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
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Computer Science > Computer Science and Game Theory arXiv:2605.15543 (cs) [Submitted on 15 May 2026] Title:Domain-Independent Game Abstraction using Word Embedding Techniques Authors:Juho Kim, Tuomas Sandholm View a PDF of the paper titled Domain-Independent Game Abstraction using Word Embedding Techniques, by Juho Kim and Tuomas Sandholm View PDF HTML (experimental) Abstract:Many games of interest in the real world are often intractably large, thereby necessitating the use of game abstraction to shrink them in size, typically by many magnitudes.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.
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