Coalition formation for Multi-agent Pursuit based on Neural Network and
  AGRMF Model
  An approach for coalition formation of multi-agent pursuit based on neural
network and AGRMF model is proposed.This paper constructs a novel neural work
called AGRMF-ANN which consists of feature extraction part and group generation
part. On one hand,The convolutional layers of feature extraction part can
abstract the features of agent group role membership function(AGRMF) for all of
the groups,on the other hand,those features will be fed to the group generation
part based on self-organizing map(SOM) layer which is used to group the
pursuers with similar features in the same group. Besides, we also come up the
group attractiveness function(GAF) to evaluate the quality of groups and the
pursuers contribution in order to adjust the main ability indicators of AGRMF
and other weight of all neural network. The simulation experiment showed that
this proposal can improve the effectiveness of coalition formation for
multi-agent pursuit and ability to adopt pursuit-evasion problem with the scale
of pursuer team growing.
