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Causal reasoning with forces.

Wolff P, Barbey AK - Front Hum Neurosci (2015)

Bottom Line: In one experiment, the force theory was uniquely able to account for people's ability to compose causal relationships from complex animations of real-world events.In three additional experiments, the force theory did as well as or better than the other two theories in explaining the causal compositions people generated from linguistically presented causal relations.Implications for causal learning and the hierarchical structure of causal knowledge are discussed.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychology, Emory University Atlanta, GA, USA.

ABSTRACT
Causal composition allows people to generate new causal relations by combining existing causal knowledge. We introduce a new computational model of such reasoning, the force theory, which holds that people compose causal relations by simulating the processes that join forces in the world, and compare this theory with the mental model theory (Khemlani et al., 2014) and the causal model theory (Sloman et al., 2009), which explain causal composition on the basis of mental models and structural equations, respectively. In one experiment, the force theory was uniquely able to account for people's ability to compose causal relationships from complex animations of real-world events. In three additional experiments, the force theory did as well as or better than the other two theories in explaining the causal compositions people generated from linguistically presented causal relations. Implications for causal learning and the hierarchical structure of causal knowledge are discussed.

No MeSH data available.


The images above each depict a scene showing a boat, a bank of fans, and a cone. In the CAUSE scene, the boat motors away from the cone, but is pushed back to the cone by the fans. In the HELP scene, the boat motors toward the cone, and the fans push it along in the same direction. In the PREVENT scene, the boat motors toward the cone, but the fans push it back away from the cone. Free-body diagrams associated with each type of causation are shown below each scene. In these diagrams, A, the affector force, P, the patient force, R, the resultant force, and E, endstate vector, which is a position vector, not a force.
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Figure 2: The images above each depict a scene showing a boat, a bank of fans, and a cone. In the CAUSE scene, the boat motors away from the cone, but is pushed back to the cone by the fans. In the HELP scene, the boat motors toward the cone, and the fans push it along in the same direction. In the PREVENT scene, the boat motors toward the cone, but the fans push it back away from the cone. Free-body diagrams associated with each type of causation are shown below each scene. In these diagrams, A, the affector force, P, the patient force, R, the resultant force, and E, endstate vector, which is a position vector, not a force.

Mentions: The force theory specifies how the notions of tendency, concordance, and progress toward the endstate can be instantiated in non-linguistic terms, namely in terms of force and position vectors. The way the theory does this is shown in Figure 2. Each scene in Figure 2 shows a situation involving a pool of water, a boat with an outboard engine, a bank of fans, and a buoy. Below each scene is a free-body diagram which makes explicit the direction and relative magnitude of the forces in each scene.


Causal reasoning with forces.

Wolff P, Barbey AK - Front Hum Neurosci (2015)

The images above each depict a scene showing a boat, a bank of fans, and a cone. In the CAUSE scene, the boat motors away from the cone, but is pushed back to the cone by the fans. In the HELP scene, the boat motors toward the cone, and the fans push it along in the same direction. In the PREVENT scene, the boat motors toward the cone, but the fans push it back away from the cone. Free-body diagrams associated with each type of causation are shown below each scene. In these diagrams, A, the affector force, P, the patient force, R, the resultant force, and E, endstate vector, which is a position vector, not a force.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4301188&req=5

Figure 2: The images above each depict a scene showing a boat, a bank of fans, and a cone. In the CAUSE scene, the boat motors away from the cone, but is pushed back to the cone by the fans. In the HELP scene, the boat motors toward the cone, and the fans push it along in the same direction. In the PREVENT scene, the boat motors toward the cone, but the fans push it back away from the cone. Free-body diagrams associated with each type of causation are shown below each scene. In these diagrams, A, the affector force, P, the patient force, R, the resultant force, and E, endstate vector, which is a position vector, not a force.
Mentions: The force theory specifies how the notions of tendency, concordance, and progress toward the endstate can be instantiated in non-linguistic terms, namely in terms of force and position vectors. The way the theory does this is shown in Figure 2. Each scene in Figure 2 shows a situation involving a pool of water, a boat with an outboard engine, a bank of fans, and a buoy. Below each scene is a free-body diagram which makes explicit the direction and relative magnitude of the forces in each scene.

Bottom Line: In one experiment, the force theory was uniquely able to account for people's ability to compose causal relationships from complex animations of real-world events.In three additional experiments, the force theory did as well as or better than the other two theories in explaining the causal compositions people generated from linguistically presented causal relations.Implications for causal learning and the hierarchical structure of causal knowledge are discussed.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychology, Emory University Atlanta, GA, USA.

ABSTRACT
Causal composition allows people to generate new causal relations by combining existing causal knowledge. We introduce a new computational model of such reasoning, the force theory, which holds that people compose causal relations by simulating the processes that join forces in the world, and compare this theory with the mental model theory (Khemlani et al., 2014) and the causal model theory (Sloman et al., 2009), which explain causal composition on the basis of mental models and structural equations, respectively. In one experiment, the force theory was uniquely able to account for people's ability to compose causal relationships from complex animations of real-world events. In three additional experiments, the force theory did as well as or better than the other two theories in explaining the causal compositions people generated from linguistically presented causal relations. Implications for causal learning and the hierarchical structure of causal knowledge are discussed.

No MeSH data available.