交互式动态影响图研究及其最优K模型解法
潘颖慧;曾一锋
【期刊名称】《计算机学报》 【年(卷),期】2018(041)001
【摘要】Multiagent sequential decision-making problem under uncertainty is an important research issue in the area of artificial intelligence,and mainly focuses on solutions to the problem of how agents shall optimize their decisions in the interactions.Particularly in a setting of partially observable,stochastic games agents can't perceive the precise states of external environmentsand rely on received observations to infer the hidden states.Meanwhile,the stochastic actions of agents have a direct influence on decisions of other agents.Their interactions
impact
the
state
changes
of
the
common
environment,which decides rewards in executing their actions.Hence the core task is to model agents' interactions and subsequently to solve the model.Most of the existing research models the entire multiagent systems and follows the mechanism of centralized plan and decentralized control to solve the problem.It first computes a joint policy for all the agents and then assigns the local policies to the agents for a final execution.This approach often demands that all the agents hold common knowledge of the global environment,which can only be applied in cooperative multiagent systems.In contrast,interactive
交互式动态影响图研究及其最优K模型解法
