DareFightingICE Competition: A Fighting Game Sound Design and AI Competition
This paper presents a new competition -- at the 2022 IEEE Conference on Games (CoG) -- called DareFightingICE Competition. The competition has two tracks: a sound design track and an AI track. The game platform for this competition is also called DareFightingICE, a fighting game platform. DareFightingICE is a sound-design-enhanced version of FightingICE, used earlier in a competition at CoG until 2021 to promote artificial intelligence (AI) research in fighting games. In the sound design track, participants compete for the best sound design, given the default sound design of DareFightingICE as a sample, where we define a sound design as a set of sound effects combined with the source code that implements their timing-control algorithm. Participants of the AI track are asked to develop their AI algorithm that controls a character given only sound as the input (blind AI) to fight against their opponent; a sample deep-learning blind AI will be provided by us. Our means to maximize the synergy between the two tracks are also described. This competition serves to come up with effective sound designs for visually impaired players, a group in the gaming community which has been mostly ignored. To the best of our knowledge, DareFightingICE Competition is the first of its kind within and outside of CoG.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Enhanced DareFightingICE Competitions: Sound Design and AI Competitions
This paper presents a new and improved DareFightingICE platform, a fighting game platform with a focus on visually impaired players (VIPs), in the Unity game engine. It also introduces the separation of the DareFightingI…
UnityA Deep Reinforcement Learning Blind AI in DareFightingICE
This paper presents a deep reinforcement learning agent (AI) that uses sound as the input on the DareFightingICE platform at the DareFightingICE Competition in IEEE CoG 2022. In this work, an AI that only uses sound as t…
Deep Reinforcement Learningreinforcement-learningReinforcement LearningReinforcement Learning (RL)Fighting Game Adaptive Background Music for Improved Gameplay
This paper presents our work to enhance the background music (BGM) in DareFightingICE by adding adaptive features. The adaptive BGM consists of three different categories of instruments playing the BGM of the winner soun…
AI AgentDeep Reinforcement LearningImproving Data Transfer Efficiency for AIs in the DareFightingICE using gRPC
This paper presents a new communication interface for the DareFightingICE platform, a Java-based fighting game focused on implementing AI for controlling a non-player character. The interface uses an open-source remote p…
Achieving Fairness in DareFightingICE Agents Evaluation Through a Delay Mechanism
This paper proposes a delay mechanism to mitigate the impact of latency differences in the gRPC framework--a high-performance, open-source universal remote procedure call (RPC) framework--between different programming la…
Decision MakingFairness