Evaluating the inverse reasoning account of object discovery
Related Experiment Video
Updated: Apr 15, 2026

Methods for Presenting Real-world Objects Under Controlled Laboratory Conditions
Published on: June 21, 2019
Christopher D Carroll1, Charles Kemp1
1Department of Psychology, Carnegie Mellon University, United States.
Abstract:
People routinely make inferences about unobserved objects. A hotel guest with welts on his arms, for example, will often worry about bed bugs. The discovery of unobserved objects almost always involves a backward inference from some observed effects (e.g., welts) to unobserved causes (e.g., bed bugs). The inverse reasoning account, which is typically formalized as Bayesian inference, posits that the strength of a backward inference is closely connected to the strength of the corresponding forward inference from the unobserved causes to the observed effects. We evaluated the inverse reasoning account of object discovery in three experiments where participants were asked to discover the unobserved "attractors" and "repellers" that controlled a "particle" moving within an arena. Experiments 1 and 2 showed that participants often failed to provide the best explanations for various particle motions, even when the best explanations were simple and when participants enthusiastically endorsed these explanations when presented with them. This failure demonstrates that object discovery is critically dependent on the processes that support hypothesis generation-processes that the inverse reasoning account does not explain. Experiment 3 demonstrated that people sometimes generate explanations that are invalid even according to their own forward inferences, suggesting that the psychological processes that support forward and backward inference are less intertwined than the inverse reasoning account suggests. The experimental findings support an alternative account of object discovery in which people rely on heuristics to generate possible explanations.
Insights
People often use heuristics, not just logical inference, to discover hidden objects. This study shows that our hypothesis generation processes, not just backward reasoning, are key to finding unobserved causes.
Area of Science:
- Cognitive Psychology
- Decision Making
- Human Reasoning
Background:
- Humans frequently infer unobserved causes from observed effects, a process crucial for understanding the world.
- The inverse reasoning account, often modeled using Bayesian inference, links backward inference strength to forward inference strength.
Purpose of the Study:
- To evaluate the inverse reasoning account of object discovery.
- To investigate the role of hypothesis generation in discovering unobserved causes.
Main Methods:
- Three experiments were conducted where participants identified unobserved 'attractors' and 'repellers' influencing a 'particle's' motion.
- Participants' ability to generate and endorse explanations for particle movements was assessed.
Main Results:
- Participants frequently failed to identify the best explanations for particle motion, even when simple and highly endorsed upon presentation.
- Experiment 3 indicated that forward and backward inference processes may be less integrated than the inverse reasoning account suggests.
Conclusions:
- Object discovery heavily relies on hypothesis generation, a process not fully explained by the inverse reasoning account.
- Heuristics play a significant role in how people generate potential explanations during object discovery.
Related Concept Videos
Inductive Reasoning
Inductive reasoning is common in descriptive science. A life scientist makes observations and records them. This data can be qualitative or...
Naturalistic Observations
Deductive Reasoning
For example, a researcher can deduce specific predictions...
Reasoning
Inductive reasoning involves deriving generalizations from specific observations. This type of reasoning helps form beliefs about the world. For example,...
Hindsight Biases
The Nativist Approach

