Micro- and macro-level validation in agent-based simulation: Reproduction of human-like behaviors and thinking in a sequential bargaining game

Keiki Takadama, Tetsuro Kawai, Yuhsuke Koyama

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)

Abstract

This paper addresses both micro- and macro-level validation in agent-based simulation (ABS) to explore validated agents that can reproduce not only human-like behaviors externally but also human-like thinking internally. For this purpose, we employ the sequential bargaining game, which can investigate a change in humans' behaviors and thinking longer than the ultimatum game (i.e., one-time bargaining game), and compare simulation results of Q-learning agents employing any type of the three types of action selections (i.e., the £greedy, roulette, and Boltzmann distribution selections) in the game. Intensive simulations have revealed the following implications: (1) Q-learning agents with any type of three action selections can reproduce human-like behaviors but not human-like thinking, which means that they are validated from the macro-level viewpoint but not from the micro-level viewpoint; and (2) Q-learning agents employing Boltzmann distribution selection with changing the random parameter can reproduce both human-like behaviors and thinking, which means that they are validated from both micro- and macro-level viewpoints.

Original languageEnglish
JournalJASSS
Volume11
Issue number2
Publication statusPublished - 2008 Mar
Externally publishedYes

Keywords

  • Agent modeling
  • Agent-based simulation
  • Micro- and macro-level validation
  • Reinforcement learning
  • Sequential bargaining game

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Social Sciences(all)

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