Automatic parameter learning method for agent activation spreading network by evolutionary computation

HIGHLIGHTS

SUMMARY

    Since some of the evolutionary computation methods adjust agents on basis of their semantics, the authors changed the names of the agents in the experimental tile world environment from abstract ones (e_g, "Planning Enemy" or "Planning Tile") to concrete ones (e_g, "Avoid Enemy" or "Go to Tile"). The first is a function that multiplies the environment information "env_info" by the agent`s intensity I as in Eq 1, where a specific value is sent as an active propagation when the condition is met (i.e., having a Tile). Note that the "env_info" is derived . . .

     

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