Communicating with Unknown Teammates
暂无分享,去创建一个
Sarit Kraus | Noa Agmon | Peter Stone | Samuel Barrett | Noam Hazon | P. Stone | Sarit Kraus | Samuel Barrett | Noam Hazon | Noam Agmon
[1] Brett Browning,et al. Dynamically formed heterogeneous robot teams performing tightly-coordinated tasks , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..
[2] Amos Azaria,et al. Combining psychological models with machine learning to better predict people’s decisions , 2012, Synthese.
[3] Joel Veness,et al. Monte-Carlo Planning in Large POMDPs , 2010, NIPS.
[4] Manuela M. Veloso,et al. Modeling mutual capabilities in heterogeneous teams for role assignment , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[5] Sarit Kraus,et al. The Evolution of Sharedplans , 1999 .
[6] Kagan Tumer,et al. Robot coordination with ad-hoc team formation , 2010, AAMAS.
[7] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[8] Sarit Kraus,et al. Teamwork with Limited Knowledge of Teammates , 2013, AAAI.
[9] David Hsu,et al. SARSOP: Efficient Point-Based POMDP Planning by Approximating Optimally Reachable Belief Spaces , 2008, Robotics: Science and Systems.
[10] Claudia V. Goldman,et al. Learning to communicate in a decentralized environment , 2007, Autonomous Agents and Multi-Agent Systems.
[11] Ming Li,et al. Soft Control on Collective Behavior of a Group of Autonomous Agents By a Shill Agent , 2006, J. Syst. Sci. Complex..
[12] Feng Wu,et al. Online Planning for Ad Hoc Autonomous Agent Teams , 2011, IJCAI.
[13] Yifeng Zeng,et al. Improved approximation of interactive dynamic influence diagrams using discriminative model updates , 2009, AAMAS.
[14] Richard S. Sutton,et al. Introduction to Reinforcement Learning , 1998 .
[15] Nan Rong,et al. What makes some POMDP problems easy to approximate? , 2007, NIPS.
[16] M. Puterman,et al. Modified Policy Iteration Algorithms for Discounted Markov Decision Problems , 1978 .
[17] David Danks,et al. Wisdom of crowds versus groupthink: learning in groups and in isolation , 2013, Int. J. Game Theory.
[18] Sarit Kraus,et al. Ad Hoc Autonomous Agent Teams: Collaboration without Pre-Coordination , 2010, AAAI.
[19] Peter Stone,et al. An analysis framework for ad hoc teamwork tasks , 2012, AAMAS.
[20] Csaba Szepesvári,et al. Bandit Based Monte-Carlo Planning , 2006, ECML.
[21] Sarit Kraus,et al. To teach or not to teach?: decision making under uncertainty in ad hoc teams , 2010, AAMAS.
[22] Vincent Conitzer,et al. AWESOME: A general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents , 2003, Machine Learning.
[23] Sarit Kraus,et al. Empirical evaluation of ad hoc teamwork in the pursuit domain , 2011, AAMAS.
[24] Emma Brunskill,et al. Bayes-optimal reinforcement learning for discrete uncertainty domains , 2012, AAMAS.
[25] Michael H. Bowling,et al. Coordination and Adaptation in Impromptu Teams , 2005, AAAI.
[26] Milind Tambe,et al. Towards Flexible Teamwork , 1997, J. Artif. Intell. Res..
[27] P. J. Gmytrasiewicz,et al. A Framework for Sequential Planning in Multi-Agent Settings , 2005, AI&M.
[28] Peter Auer,et al. Finite-time Analysis of the Multiarmed Bandit Problem , 2002, Machine Learning.
[29] David Carmel,et al. Incorporating Opponent Models into Adversary Search , 1996, AAAI/IAAI, Vol. 1.