---
title: "The RoboCup Synthetic Agent Challenge 97"
authors:
  - "Hiroaki Kitano"
  - "Milind Tambe"
  - "Peter Stone"
  - "Manuela M. Veloso"
  - "Silvia Coradeschi"
  - "Eiichi Osawa"
  - "Hitoshi Matsubara"
  - "Itsuki Noda"
  - "Minoru Asada"
doi: ""
url: "https://ijcai.org/proceedings/1997/4"
pdf: "https://ijcai.org/proceedings/1997/0004.pdf"
venue: "Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence"
year: 1997
pages: "24-29"
track: "AI Challenges"
keywords:
---

# The RoboCup Synthetic Agent Challenge 97

Hiroaki Kitano, Milind Tambe, Peter Stone, Manuela M. Veloso, Silvia Coradeschi, Eiichi Osawa, Hitoshi Matsubara, Itsuki Noda, Minoru Asada

*Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence*, pages 24-29.

## Abstract

RoboCup Challenge offers a set of challenges for intelligent agent researchers using a friendly competition in a dynamic, real-time, multiagent domain. While RoboCup in general envisions longer range challenges over the next few decades, RoboCup Challenge presents three specific challenges for the next two years: (i) learning of individual agents and teams; (ii) multi-agent team planning and plan-execution in service of teamwork; and (iii) opponent modeling. RoboCup Challenge provides a novel opportunity for machine learning, planning, and multi-agent researchers - it not only supplies a concrete domain to evalute their techniques, but also challenges researchers to evolve these techniques to face key constraints fundamental to this domain: real-time, uncertainty, and teamwork.