paper-with-me

Papers

Towards automating Codenames spymasters with deep reinforcement learning

2022-12-28 · Sherman Siu

Although most reinforcement learning research has centered on competitive games, little work has been done on applying it to co-operative multiplayer games or text-based games. Codenames is a board game that involves both asymmetric co-operation and natural language processing, which makes it an excellent candidate for advancing RL research. To my knowledge, this work is the first to formulate Codenames as a Markov Decision Process and apply some well-known reinforcement learning algorithms such as SAC, PPO, and A2C to the environment. Although none of the above algorithms converge for the Codenames environment, neither do they converge for a simplified environment called ClickPixel, except when the board size is small.

📄 PDF Abstract BibTeX arXiv:2212.14104

Code (0)

등록된 구현이 없습니다.

Tasks

Deep Reinforcement Learningreinforcement-learningReinforcement LearningReinforcement Learning (RL)text-based games

Methods 이 논문이 사용한 방법론

None 설명 없음
Dilated Convolution 설명 없음
Convolution A convolution is a type of matrix operation, consisting of a kernel, a small matrix of weights, that slides over input data performing element-wise multiplication with the…
Global Average Pooling Global Average Pooling is a pooling operation designed to replace fully connected layers in classical CNNs. The idea is to generate one feature map for each corresponding…
1x1 Convolution A 1 x 1 Convolution is a convolution with some special properties in that it can be used for dimensionality reduction,…
Average Pooling 설명 없음
SAC 설명 없음
A2C A2C, or Advantage Actor Critic, is a synchronous version of the A3C policy gradient method. As an alternative to the asynchronous…

Similar Papers 제목 키워드 기반

Communicate to Play: Pragmatic Reasoning for Efficient Cross-Cultural Communication in Codenames

2024-08-09 · Isadora White, Sashrika Pandey, Michelle Pan

Cultural differences in common ground may result in pragmatic failure and misunderstandings during communication. We develop our method Rational Speech Acts for Cross-Cultural Communication (RSA+C3) to resolve cross-cult…

Contrastive Learning

Codenames as a Benchmark for Large Language Models

2024-12-16 · Matthew Stephenson, Matthew Sidji, Benoît Ronval

In this paper, we propose the use of the popular word-based board game Codenames as a suitable benchmark for evaluating the reasoning capabilities of Large Language Models (LLMs). Codenames presents a highly interesting …

Epistemic Reasoning

Playing Codenames with Language Graphs and Word Embeddings

2021-05-12 · Divya Koyyalagunta, Anna Sun, Rachel Lea Draelos, Cynthia Rudin

Although board games and video games have been studied for decades in artificial intelligence research, challenging word games remain relatively unexplored. Word games are not as constrained as games like chess or poker.…

Board GamesCommon Sense ReasoningWord Embeddings

Codenames as a Game of Co-occurrence Counting

2022-05-01 · CMCL (ACL) 2022 5 · Réka Cserháti, Istvan Kollath, András Kicsi, Gábor Berend

Codenames is a popular board game, in which knowledge and cooperation between players play an important role. The task of a player playing as a spymaster is to find words (clues) that a teammate finds related to as many …

Ad-hoc Concept Forming in the Game Codenames as a Means for Evaluating Large Language Models

2025-02-17 · Sherzod Hakimov, Lara Pfennigschmidt, David Schlangen

This study utilizes the game Codenames as a benchmarking tool to evaluate large language models (LLMs) with respect to specific linguistic and cognitive skills. LLMs play each side of the game, where one side generates a…

Benchmarking