PDF Viewer

BUILDER'S SANDBOX

Build This Paper

Use an AI coding agent to implement this research.

OpenAI Codex
OpenAI CodexAI Agent

Lightweight coding agent in your terminal.

Claude Code
Claude CodeAI Agent

Agentic coding tool for terminal workflows.

AntiGravity IDE
AntiGravity IDEScaffolding

AI agent mindset installer and workflow scaffolder.

Cursor
CursorIDE

AI-first code editor built on VS Code.

VS Code
VS CodeIDE

Free, open-source editor by Microsoft.

Estimated $9K - $13K over 6-10 weeks.

See exactly what it costs to build this -- with 3 comparable funded startups.

7-day free trial. Cancel anytime.

Discover the researchers behind this paper and find similar experts.

7-day free trial. Cancel anytime.

References (21)

[1]
Modeling Uncertainty: Constraint-Based Belief States in Imperfect-Information Games
2025Achille Morenville, Éric Piette
[2]
GameTable COST action: kickoff report
2024Éric Piette, Walter Crist et al.
[3]
Belief Stochastic Game: A Model for Imperfect-Information Games with Known Positions
2024Achille Morenville, Éric Piette
[4]
Monte Carlo Tree Search: a review of recent modifications and applications
2021M. Świechowski, K. Godlewski et al.
[5]
Quantifying the Space of Hearts Variants
2021Mark H. Goadrich, Collin Shaddox
[6]
TAG: A Tabletop Games Framework
2020Raluca D. Gaina, Martin Balla et al.
[7]
Emulating Human Play in a Leading Mobile Card Game
2019Hendrik Baier, Adam Sattaur et al.
[8]
RLCard: A Toolkit for Reinforcement Learning in Card Games
2019D. Zha, Kwei-Herng Lai et al.
[9]
OpenSpiel: A Framework for Reinforcement Learning in Games
2019Marc Lanctot, Edward Lockhart et al.
[10]
Survey of Artificial Intelligence for Card Games and Its Application to the Swiss Game Jass
2019Joel Niklaus, Michele Alberti et al.
[11]
Deep Counterfactual Regret Minimization
2018Noam Brown, Adam Lerer et al.
[12]
Application of Self-Play Reinforcement Learning to a Four-Player Game of Imperfect Information
2018Henry Charlesworth
[13]
Automated Playtesting with RECYCLEd CARDSTOCK
2016Connor Bell
[14]
A Doppelkopf Player Based on UCT
2015Silvan Sievers, M. Helmert
[15]
Determinization and information set Monte Carlo Tree Search for the card game Dou Di Zhu
2011D. Whitehouse, E. Powley et al.
[16]
GIB: Imperfect Information in a Computationally Challenging Game
2011Matthew L. Ginsberg
[17]
Improving State Evaluation, Inference, and Search in Trick-Based Card Games
2009M. Buro, J. Long et al.
[18]
Regret Minimization in Games with Incomplete Information
2007Martin A. Zinkevich, Michael Bradley Johanson et al.
[19]
An Analysis of Alpha-Beta Priming '
2002D. Knuth, Ronald W. Moore
[20]
Games with Imperfect Information
1993J. Blair, D. Mutchler et al.

Showing 20 of 21 references

Founder's Pitch

"Valet is a standardized testbed for benchmarking AI algorithms on traditional imperfect-information card games."

AI BenchmarkingScore: 5View PDF ↗

Commercial Viability Breakdown

0-10 scale

High Potential

1/4 signals

2.5

Quick Build

4/4 signals

10

Series A Potential

1/4 signals

2.5

Sources used for this analysis

arXiv Paper

Full-text PDF analysis of the research paper

GitHub Repository

Code availability, stars, and contributor activity

Citation Network

Semantic Scholar citations and co-citation patterns

Community Predictions

Crowd-sourced unicorn probability assessments

Analysis model: GPT-4o · Last scored: 3/3/2026

Explore the full citation network and related research.

7-day free trial. Cancel anytime.

Understand the commercial significance and market impact.

7-day free trial. Cancel anytime.

Get detailed profiles of the research team.

7-day free trial. Cancel anytime.