In the 1930s and 1940s, Edward Tolman developed a psychological theory of spatial orientation in rats and humans. He expressed his theory as an automaton (the ‘‘schematic sowbug’’) or what today we would call an ‘‘artificial organism.’’ With the technology of the day, he could not implement his model. Nonetheless, he used it to develop empirical predictions which tested with animals in the laboratory. This way of proceeding was in line with scientific practice dating back to Galileo. The way psychologists use artificial organisms in their work today breaks with this tradition. Modern ‘‘artificial organisms’’ are constructed a posteriori, working from experimental or ethological observations. As a result, researchers can use them to confirm a theoretical model or to simulate its operation. But they make no contribution to the actual building of models. In this paper, we try to return to Tolman’s original strategy: implementing his theory of ‘‘vicarious trial and error’’ in a simulated robot, forecasting the robot’s behavior and conducting experiments that verify or falsify these predictions.

Artificial organisms as tools for the development of psychological theory: Tolman's lesson

MIGLINO, ORAZIO;GIGLIOTTA, Onofrio;PONTICORVO, MICHELA
2007

Abstract

In the 1930s and 1940s, Edward Tolman developed a psychological theory of spatial orientation in rats and humans. He expressed his theory as an automaton (the ‘‘schematic sowbug’’) or what today we would call an ‘‘artificial organism.’’ With the technology of the day, he could not implement his model. Nonetheless, he used it to develop empirical predictions which tested with animals in the laboratory. This way of proceeding was in line with scientific practice dating back to Galileo. The way psychologists use artificial organisms in their work today breaks with this tradition. Modern ‘‘artificial organisms’’ are constructed a posteriori, working from experimental or ethological observations. As a result, researchers can use them to confirm a theoretical model or to simulate its operation. But they make no contribution to the actual building of models. In this paper, we try to return to Tolman’s original strategy: implementing his theory of ‘‘vicarious trial and error’’ in a simulated robot, forecasting the robot’s behavior and conducting experiments that verify or falsify these predictions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/106196
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