Just say no: how are visual searches terminated when there is no target present?

How should a visual search task be terminated when no target is found? Such searches could end after a serial search through all items, but blank trials in many tasks are terminated too quickly for that to be plausible. This paper proposes a solution based on Wolfe's (1994) Guided Search model. The probability that each item is a target is computed in parallel based on items' differences from each other and their similarity to the desired target. This probability is expressed as an activation. Activations are examined in decreasing order until the target is found or until an activation threshold is reached. This threshold is set adaptively by the observer--more conservative following misses, more liberal following successful trials. In addition, observers guess on some trials. The probability of a guess increases as trial duration increases. The model successfully explains blank trial performance. Specific predictions are tested by experiments.