Extended behavior networks and agent personality: investigating the design of character stereotypes in the game Unreal Tournament

  • Authors:
  • Hugo da Silva Corrêa Pinto;Luis Otávio Alvares

  • Affiliations:
  • Instituto de Informática - Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre - RS, Brazil;Instituto de Informática - Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre - RS, Brazil

  • Venue:
  • Lecture Notes in Computer Science
  • Year:
  • 2005

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Abstract

The Extended Behavior Network (EBN) is an architecture and action selection mechanism to design agents capable of selecting sets of concurrent actions in dynamic and continuous environments. It allows one to specify context-dependent motivations and build agents modularly, and has achieved good results in the Robocup and in the 3D action game Unreal Tournament. PHISH-Nets, another behavior network model capable of selecting just single actions, was applied to character modeling, with promising results. We investigate how EBNs fare on agent personality modeling via the design and analysis of 5 stereotypes in Unreal Tournament. We discuss three ways to build character personas and situate our work within other approaches. We conclude that EBNs provide a straightforward way to develop and experiment with different personalities, being interesting for building agents with simple personas and for character prototyping.