基于马尔可夫决策过程的社团演化干预

社团的演化往往是复杂多变的，如何对这些嵌入在网络中的社团进行个性化干预，使得不同的社团朝着不同的既定方向演化的研究逐渐成为社交网络领域的一个重要问题.在社团演化的干预框架下，基于状态转移视角，提出了基于马尔可夫决策过程的社团演化干预模型.该模型通过对社团状态维度分数与干预目标的综合考虑，确立社团演化过程与马尔可夫决策过程的对应关系，对社团演化中的状态、动作、回报进行精细建模，同时将社团演化期望回报与研究者的奖励相对应，对马尔可夫决策过程求解，实现对社团演化的干预.在不同社团数据集上的实验结果表明，基于马尔可夫决策过程的干预模型能够对社团的演化进行有效的干预.

The Intervention of Community Evolution Based on Markov Decision Process

The evolution of the community always tends to be complex and changeable. It becomes an important issue in the field of social networks about how to conduct personalized intervention on communities which are embedded in the network and make different communities evolve toward to different aims. Based on the intervention framework of community evolution， an intervention model based on Markov decision process(MDP)was proposed with the perspective of state transition. With the score of the state dimension and intervention goal， this model establishes the corresponding relationship between the evolution process and MDP， and then models the state， action， and reward in evolution process. Meanwhile， the expected reward of community evolution corresponds to the researcher′s reward. By solving the MDP， the community evolution can be effectively intervened. The experiment results indicated that the community evolution intervention model based on MDP can intervene the community evolution on different true data sets.