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Heuristic Selection of Actions in Multiagent Reinforcement Learning ∗
"... This work presents a new algorithm, called Heuristically Accelerated Minimax-Q (HAMMQ), that allows the use of heuristics to speed up the wellknown Multiagent Reinforcement Learning algorithm Minimax-Q. A heuristic function H that influences the choice of the actions characterises the HAMMQ algorith ..."
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This work presents a new algorithm, called Heuristically Accelerated Minimax-Q (HAMMQ), that allows the use of heuristics to speed up the wellknown Multiagent Reinforcement Learning algorithm Minimax-Q. A heuristic function H that influences the choice of the actions characterises the HAMMQ
