# Introducing Tales of Tribute AI Competition

arXiv: https://arxiv.org/abs/2305.08234 · HTML: https://mlsanity.com/paper/2305.08234/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 31 references that are in the map.
- First posted on arXiv 14 May 2023.

## Builds on (most cited first, 10 of 10)

- [Mapping Hearthstone Deck Spaces through MAP-Elites with Sliding Boundaries](https://mlsanity.com/paper/1904.10656/) (2019)
- [Improving Hearthstone AI by Combining MCTS and Supervised Learning Algorithms](https://mlsanity.com/paper/1808.04794/) (2018)
- [The Many AI Challenges of Hearthstone](https://mlsanity.com/paper/1907.06562/) (2019)
- [Introducing the Hearthstone-AI Competition](https://mlsanity.com/paper/1906.04238/) (2019)
- [Mastering Strategy Card Game (Legends of Code and Magic) via End-to-End Policy and Optimistic Smooth Fictitious Play](https://mlsanity.com/paper/2303.04096/) (2023)
- [Mastering Strategy Card Game (Hearthstone) with Improved Techniques](https://mlsanity.com/paper/2303.05197/) (2023)
- [Evolving the Hearthstone Meta](https://mlsanity.com/paper/1907.01623/) (2019)
- [Evolving Evaluation Functions for Collectible Card Game AI](https://mlsanity.com/paper/2105.01115/) (2021)
- [AI Researchers, Video Games Are Your Friends!](https://mlsanity.com/paper/1612.01608/) (2016)
- [Developing a Successful Bomberman Agent](https://mlsanity.com/paper/2203.09608/) (2022)

## Built on by (most cited first, 2 of 2)

- [Summarizing Strategy Card Game AI Competition](https://mlsanity.com/paper/2305.11814/) (2023)
- [A Taxonomy of Collectible Card Games from a Game-Playing AI Perspective](https://mlsanity.com/paper/2410.06299/) (2024)

## Abstract (arXiv)

This paper presents a new AI challenge, the Tales of Tribute AI Competition (TOTAIC), based on a two-player deck-building card game released with the High Isle chapter of The Elder Scrolls Online. Currently, there is no other AI competition covering Collectible Card Games (CCG) genre, and there has never been one that targets a deck-building game. Thus, apart from usual CCG-related obstacles to overcome, like randomness, hidden information, and large branching factor, the successful approach additionally requires long-term planning and versatility. The game can be tackled with multiple approaches, including classic adversarial search, single-player planning, and Neural Networks-based algorithms. This paper introduces the competition framework, describes the rules of the game, and presents the results of a tournament between sample AI agents.