ChatGPT4PCG Competition: Character-like Level Generation for Science Birds

Abstract

This paper presents the first ChatGPT4PCG Competition at the 2023 IEEE Conference on Games. The objective of this competition is for participants to create effective prompts for ChatGPT-enabling it to generate Science Birds levels with high stability and character-like qualities-fully using their creativity as well as prompt engineering skills. ChatGPT is a conversational agent developed by OpenAI. Science Birds is selected as the competition platform because designing an Angry Birds-like level is not a trivial task due to the in-game gravity; the playability of the levels is determined by their stability. To lower the entry barrier to the competition, we limit the task to the generation of capitalized English alphabetical characters. Here, the quality of the generated levels is determined by their stability and similarity to the given characters. A sample prompt is provided to participants for their reference. An experiment is conducted to determine the effectiveness of its modified versions on level stability and similarity by testing them on several characters. To the best of our knowledge, we believe that ChatGPT4PCG is the first competition of its kind and hope to inspire enthusiasm for prompt engineering in procedural content generation.

Assessing GPT-4’s Role as a Co-Collaborator in Scientific Research: A Case Study Analyzing Einstein’s Special Theory of Relativity

“…into the importance of prompt engineering, the development of frameworks and strategies for structuring prompts, and the evaluation of LLM performance on complex tasks. 5,6,[24][25][26][27][28][29] These studies highlight the significance of prompt engineering when working with models like GPT-4 and provide relevant context for using LLMs in advanced research, such as the present study on SRT. This work differs from these studies in that it specifically evaluates GPT-4, which is posited to possess emergent, foundational AGI behaviors.…”

Assessing GPT-4’s Role as a Co-Collaborator in Scientific Research: A Case Study Analyzing Einstein’s Special Theory of Relativity

“…White et al, Sorensen et into the importance of prompt engineering, the development of frameworks and strategies for structuring prompts, and the evaluation of LLM performance on complex tasks. [5,6,[24][25][26][27][28][29] Their works provide a pivotal scaffold for advanced research applications of LLMs, as demonstrated in the current study.…”

Physics-Based Task Generation through Causal Sequence of Physical Interactions

“…Numerous research studies have explored various methods for creating game levels in Angry Birds. Prior investigations have tackled this problem from diverse angles, proposing solutions to intriguing challenges, such as generating stable structures within the physical environment , dynamically adjusting the game levels' difficulty (Stephenson and Renz 2019), creating block structures based on hand-drawn sketches (Stephenson et al 2021), generating deceptive levels to deceive AI agents (Gamage et al 2021a), generating novel scenarios for physics environments (Gamage et al 2023(Gamage et al , 2021b and, most recently, using prompt engineering to create prompts for level generation (Taveekitworachai et al 2023). None of the previous studies has treated the level generation for Angry Birds as a task generation problem that incorporates the physical interactions between the game objects.…”