A mind needs papers like a sword needs a whetstone - Skalwalker/MRLCommunication GitHub Wiki

This page provides a simple list of articles and is intended to be a starter for people who don't know much or doesn't have any knowledge in Multiagents Systems, Artificial Intelligence, Communication in MAS, Probabilistic Robots and Machine Learning. Although there are some suggestions in this page, this might not be enough depending on your purpose.

References about Multiagent Systems

  • Stone, Peter and Veloso, Manuela. “Multiagent systems: A survey from a machine learning perspective.” Autonomous Robots 8.3 (2000): 345-383.

  • Weiss, Gerhard. “Multiagent systems: a modern approach to distributed artificial intelligence.” MIT press, 1999.

  • Panait, Liviu, and Luke, Sean. “Cooperative multi-agent learning: The state of the art.” Autonomous agents and multi-agent systems 11.3 (2005): 387-434.

  • Arai, Tamio, and Pagello, Enrico, and Parker, Lynne E. “Editorial: Advances in multi-robot systems.” IEEE Transactions on robotics and automation 18.5 (2002): 655-661

References about Probabilistic Robotics and Bayesian Programming

  • Thrun, Sebastian and Burgard, Wolfram and Fox, Dieter. “Probabilistic Robotics.” [S.l.]: MIT press, 2005.

  • Lebeltel, Olivier and Bessière, Pierre and Diard, Julien and Mazer, Emmanuel. “Bayesian robot programming” Autonomous Robots 16.1 (2004): 49-79.

  • Koike, Carla M. C. E. C. “Bayesian Approach to Action Selection and Attention Focusing. An Application in Autonomous Robot Program- ming.” Diss. Institut National Polytechnique de Grenoble-INPG, 2005.

  • Lebeltel, Olivier, and Bessière, Pierre, and Diard, Julien, and Mazer, Emmanuel. “Bayesian robot programming.” Autonomous Robots 16.1 (2004): 49-79.

References about Artificial Intelligence and Reinforcement Learning

  • Russell, Stuart and Norvig, Peter “Artificial Intelligence: A modern approach.” Artificial Intelligence. Prentice-Hall, Englewood Cliffs 25 (1995): 27.

  • Sutton, Richard S. and Andrew G. Barto. “Reinforcement learning: An introduction.” Vol. 1. No. 1. Cambridge: MIT press, 1998.

  • Mataric, MajaJ. “Reinforcementlearninginthemulti-robotdomain.” Autonomous Robots 4.1 (1997): 73-83.

References about Communication on MAS

  • Balch, Tucker and Arkin, Ronald C. “Communication in reactive multi- agent robotic systems.” Autonomous robots 1.1 (1994): 27-52.

  • Mataric, Maja J. “Using communication to reduce locality in distributed multiagent learning.” Journal of experimental & theoretical artificial intelligence 10.3 (1998): 357-369.

  • Kaiser, M. and Dillman, R. and Rogalla, O. “Communication as the basis for learning in multi-agent systems.” ECAI’96 Workshop on Learning in Distributed AI Systems. 1996.

Extra References

  • Stone, Peter and Veloso, Manuela. “Task decomposition, dynamic role assignment, and low-bandwidth communication for real-time strategic teamwork.” Artificial Intelligence 110.2 (1999): 241-273.

  • Bussab, Wilton de O. and Pedro A. Morettin. “Estatística básica.” Saraiva, 2010.

  • Tikhanoff, Vadim, and Cangelosi, Angelo, and Fitzpatrick, Paul, and Metta, Giorgio, and Natale, Lorenzo, and Nori, Francesco. “An open- source simulator for cognitive robotics research: the prototype of the iCub humanoid robot simulator.” Proceedings of the 8th workshop on performance metrics for intelligent systems. ACM, 2008.