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A Multiagent Approach to Hyper-Redundant Manipulators, , and . Proceedings of the AAMAS 2008 Workshop on Adaptive Learning Agents and Multi-Agent Systems (ALAMAS+ALAg 2008), Estoril, Portugal, (May 2008)Reinforcement Learning in Multi-agent Games - A value iteration perspective. (2007)Forecast-Based Mechanisms for Demand Response., , and . AAMAS, page 1600-1608. International Foundation for Autonomous Agents and Multiagent Systems, (2019)Addressing Environment Non-Stationarity by Repeating Q-learning Updates., and . J. Mach. Learn. Res., (2016)The value of online information for demand response in Walrasian electricity markets., , , and . ISGT Asia, page 1-6. IEEE, (2015)Towards a Fast Detection of Opponents in Repeated Stochastic Games., and . AAMAS Workshops (Selected Papers), volume 10642 of Lecture Notes in Computer Science, page 239-257. Springer, (2017)Addressing the policy-bias of q-learning by repeating updates., and . AAMAS, page 1045-1052. IFAAMAS, (2013)Bee-inspired foraging in an embodied swarm., , , , , , , and . AAMAS, page 1311-1312. IFAAMAS, (2011)Efficient balancing by effort-based activation of demand response services., , and . ISGT Europe, page 1-6. IEEE, (2016)Empirical and Theoretical Support for Leniency in Cooperative Games (Extended abstract), , and . Proc. of 10th Intl. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2011), page 1105--1106. International Foundation for AAMAS, (2011)