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Solving Motion and Action Planning for a Cooperative Agent Problem Using Geometry Friends

Part of the Lecture Notes in Computer Science book series (LNAI,volume 11804)


In this paper we discuss the development of agents for the Geometry Friends game, which poses simultaneously problems of planning and motion control in an physics-based puzzle and platform 2D world. The game is used in a competition, held yearly, that challenges participants to solve single player and cooperative levels. Our work addresses the two. The approach followed uses Rapidly-Exploring Random Trees with strategies to accelerate the search. When comparing with other agents on the competition, our results show that our agents can solve the single player challenges without overspecialization and are also promising for the cooperative levels with either agent-agent and human-agent players.


  • Artificial agent
  • Rapidly-Exploring Random Trees
  • Motion planning
  • Motion control
  • Replanning
  • Human-agent cooperation

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  • DOI: 10.1007/978-3-030-30241-2_8
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This work was supported by national funds through Fundação para a Ciência e a Tecnologia (FCT-UID/CEC/50021/2019) and through the project AMIGOS (PTDC/EEISII/7174/2014).

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Correspondence to Ana Salta .

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Salta, A., Prada, R., Melo, F. (2019). Solving Motion and Action Planning for a Cooperative Agent Problem Using Geometry Friends. In: Moura Oliveira, P., Novais, P., Reis, L. (eds) Progress in Artificial Intelligence. EPIA 2019. Lecture Notes in Computer Science(), vol 11804. Springer, Cham.

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