PARLEY AS AN APPROACH TO DISTRIBUTED DETECTION

Decentralized detection networks implement local likelihood ratio test s at each sensor and combine the local decisions into a global decisio n In general this is a ''one pass'' procedure, with data transmission from the sensors (or subordinate decision makers) to the fusion center . There have been treatments of multipass schemes, but usually the app roach has been to update the local decisions based on the previous fus ed decision. We explore the use of feedback (of all sensor decisions t o all sensors) and successive retesting and rebroadcasting of the upda ted decisions until a common decision or consensus is reached, an oper ation we call parley due to its similarity to the process of discussio n and negotiation by a team of human decision makers. We consider two modes of operation of such a network. In the first, all sensors are as correct as possible at all times. We see that this network is fast in reaching consensus, but not particularly as ''correct'' as it could b e. Under the second scheme, we observe that via feedback it is possibl e for the network to make an optimum decision-this may, of course, req uire several rounds of parley. Of particular interest is that under bo th schemes a consensus always occurs-the sensors never ''agree to disa gree''.