mlsanityData to 14 Oct 2026

Summarizing Strategy Card Game AI Competition

arXiv 2305.11814 ↗First posted 19 May 2023cs.AIcited by 7

Not on the map. Why?

Abstract (arXiv)

This paper concludes five years of AI competitions based on Legends of Code and Magic (LOCM), a small Collectible Card Game (CCG), designed with the goal of supporting research and algorithm development. The game was used in a number of events, including Community Contests on the CodinGame platform, and Strategy Card Game AI Competition at the IEEE Congress on Evolutionary Computation and IEEE Conference on Games. LOCM has been used in a number of publications related to areas such as game tree search algorithms, neural networks, evaluation functions, and CCG deckbuilding. We present the rules of the game, the history of organized competitions, and a listing of the participant and their approaches, as well as some general advice on organizing AI competitions for the research community. Although the COG 2022 edition was announced to be the last one, the game remains available and can be played using an online leaderboard arena.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 14 of its 39 references that are in the map. First posted on arXiv 19 May 2023.

Builds on

14 of 39 references.

References · 14

  1. 2017Attention Is All You Needcited by 60,361
  2. 2019Mapping Hearthstone Deck Spaces through MAP-Elites with Sliding Boundariescited by 32
  3. 2021Deep Surrogate Assisted MAP-Elites for Automated Hearthstone Deckbuildingcited by 26
  4. 2018Improving Hearthstone AI by Combining MCTS and Supervised Learning Algorithmscited by 13
  5. 2019The Many AI Challenges of Hearthstonecited by 12
  6. 2019Introducing the Hearthstone-AI Competitioncited by 10
  7. 2023Mastering Strategy Card Game (Legends of Code and Magic) via End-to-End Policy and Optimistic Smooth Fictitious Playcited by 10
  8. 2023Mastering Strategy Card Game (Hearthstone) with Improved Techniquescited by 10
  9. 2019Evolving the Hearthstone Metacited by 8
  10. 2020Evolutionary Approach to Collectible Card Game Arena Deckbuilding using Active Genescited by 7
  11. 2021Evolving Evaluation Functions for Collectible Card Game AIcited by 6
  12. 2017Helping AI to Play Hearthstone: AAIA'17 Data Mining Challengecited by 4
2 more
  1. 2016Rolling Horizon Coevolutionary Planning for Two-Player Video Gamescited by 3
  2. 2023Introducing Tales of Tribute AI Competitioncited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 4; 2025: 1; 2026: 2.

7 papers.

  1. 2024Large Language Models as Agents in Two-Player Gamescited by 10
  2. 2024Learning With Generalised Card Representations for "Magic: The Gathering"cited by 3
  3. 2025UrzaGPT: LoRA-Tuned Large Language Models for Card Selection in Collectible Card Gamescited by 2
  4. 2024Learning to Beat ByteRL: Exploitability of Collectible Card Game Agentscited by 1
  5. 2026Causal Reinforcement Learning for Complex Card Games: A Magic The Gathering Benchmarkcited by 1
  6. 2024A Taxonomy of Collectible Card Games from a Game-Playing AI Perspectivecited by 0
  7. 2026Unsound Search with Policy and Value Networks in Legends of Code and Magiccited by 0