Matching and maximizing with concurrent ratio-interval schedules.

Wallander et al. (1983) set up two schedules side by side. One paid off after a set number of responses. The other paid off after the first response in a time window.

They removed anything that let the animal loaf between responses. Then they watched which side the animal picked.

When downtime was gone, the animals shifted toward the key that moved both schedules forward. The choice fit a maximize-reinforcers rule, not a simple match-rates rule.

Fovel et al. (1989) ran almost the same VR-VI setup with mice and also saw maximization. The 1983 result held up across species.

Savastano et al. (1994) tried the same VR-VI arrangement with adult humans. People only leaned toward the ratio side; they did not fully maximize. The animal finding extends to humans, but the effect is weaker.

Yuwiler et al. (1992) used VI-VI schedules and saw no maximization at all. The positive maximization result seems tied to the VR-VI mix, not to every concurrent schedule.

If you run concurrent schedules in a token economy or choice assessment, strip out dead time. Once leisure cues are gone, clients may shift toward the option that speeds overall payoff. Try cutting wait time between tasks and watch whether the learner’s preference moves to the richer, faster track.