On the Development of Intelligent Agents for MOBA Games
This addresses the need for effective agents to play with or against humans in MOBA games, but it appears incremental as it builds on existing Influence Maps methods.
The paper tackled the problem of developing intelligent agents for MOBA games by implementing a two-layered architecture using Influence Maps, and experiments in League of Legends showed promising results in a dynamic real-time context.
Multiplayer Online Battle Arena (MOBA) is one of the most played game genres nowadays. With the increasing growth of this genre, it becomes necessary to develop effective intelligent agents to play alongside or against human players. In this paper we address the problem of agent development for MOBA games. We implement a two-layered architecture agent that handles both navigation and game mechanics. This architecture relies on the use of Influence Maps, a widely used approach for tactical analysis. Several experiments were performed using {\em League of Legends} as a testbed, and show promising results in this highly dynamic real-time context.