The IFAAMAS Influential paper award committee, chaired by Prof Carles Sierra (Other members: Elisabeth André, Kate Larson, Jaime Sichman, Gerhard Weiss), has recommended the following two papers for the 2019 award:
- Bernstein, D. S., Zilberstein, S., & Immerman, N. (2000, June). The complexity of decentralized control of Markov decision processes. In Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence (pp. 32-37).
- Bernstein, D. S., Givan, R., Immerman, N., & Zilberstein, S. (2002). The complexity of decentralized control of Markov decision processes. Mathematics of operations research, 27(4), 819-840.
These papers formally introduced the decentralized partially observable Markov decision process (Dec-POMDP), launching a subfield on principled models and solution methods for multiple cooperative agents with uncertainty and limited communication. Since then, the influence of the paper has spread widely and was followed by numerous other publications that include many theses, journal articles, conference papers and a recent book. Authors inspired by the original Dec-POMDP paper have won awards in AI conferences such as the best paper award at AAMAS in 2003 and 2014, a nomination for best student paper at AAMAS in 2011, an outstanding student paper honorable mention at AAAI 2019 as well as a nomination for best paper at one of the leading robotics conferences (RSS) in 2015. Dec-POMDP methods have become well known in the AI community (e.g., becoming a popular model for deep multi-agent reinforcement learning) and have begun to be used in fields such as robotics and networking.