# Exploring Decision-Making Capabilities of LLM Agents: An Experimental Study on Jump-Jump Game

## TL;DR

This paper investigates the decision-making abilities of large language model (LLM) agents through an experimental study using the Jump-Jump game, which tests spatial reasoning, physical modeling, and strategic planning.

## Contribution

It introduces an experimental framework for evaluating LLM decision-making in a challenging casual game environment, highlighting the models' capabilities and limitations.

## Key findings

- LLMs can perform basic spatial reasoning in the game.
- Decision accuracy varies with game complexity.
- Insights into LLMs' strategic planning abilities.

## Abstract

The Jump-Jump game, as a simple yet challenging casual game, provides an ideal testing environment for studying LLM decision-making capabilities. The game requires players to precisely control jumping force based on current position and target platform distance, involving multiple cognitive aspects including spatial reasoning, physical modeling, and strategic planning. It illustrates the basic gameplay mechanics of the Jump-Jump game, where the player character (red circle) must jump across platforms with appropriate force to maximize score.