The 2017 AIBIRDS Competition
This paper presents an overview of the sixth AIBIRDS competition, held at the 26th International Joint Conference on Artificial Intelligence. This competition tasked participants with developing an intelligent agent which can play the physics-based puzzle game Angry Birds. This game uses a sophisticated physics engine that requires agents to reason and predict the outcome of actions with only limited environmental information. Agents entered into this competition were required to solve a wide assortment of previously unseen levels within a set time limit. The physical reasoning and planning required to solve these levels are very similar to those of many real-world problems. This year's competition featured some of the best agents developed so far and even included several new AI techniques such as deep reinforcement learning. Within this paper we describe the framework, rules, submitted agents and results for this competition. We also provide some background information on related work and other video game AI competitions, as well as discussing some potential ideas for future AIBIRDS competitions and agent improvements.
Code (0)
등록된 구현이 없습니다.
Tasks
Deep Reinforcement LearningReinforcement LearningSimilar Papers 제목 키워드 기반
Deep Q-Network for Angry Birds
Angry Birds is a popular video game in which the player is provided with a sequence of birds to shoot from a slingshot. The task of the game is to destroy all green pigs with maximum possible score. Angry Birds appears t…
Decision MakingDeep Reinforcement LearningReinforcement LearningSequential Decision MakingTowards A Theory-Of-Mind-Inspired Generic Decision-Making Framework
Simulation is widely used to make model-based predictions, but few approaches have attempted this technique in dynamic physical environments of medium to high complexity or in general contexts. After an introduction to t…
Decision MakingArtificial Intelligence Security Competition (AISC)
The security of artificial intelligence (AI) is an important research area towards safe, reliable, and trustworthy AI systems. To accelerate the research on AI security, the Artificial Intelligence Security Competition (…
Autonomous DrivingFace RecognitionFace SwappingEnhanced 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…
UnityInternational Multicultural Name Matching Competition: Design, Execution, Results, and Lessons Learned
This paper describes different aspects of an open competition to evaluate multicultural name matching software, including the contest design, development of the test data, different phases of the competition, behavior of…
Transliteration