This article reports the results of an experiment addressing extrapolation in function learning, in particular the issue of whether participants can extrapolate in a nonmonotonic manner. Existing models of function learning, including the extrapolation association model of function learning (EXAM; E. L. DeLosh, J. R. Busemeyer, & M. A. McDaniel, 1997), cannot account for this type of extrapolation pattern. We present the results of an experiment in which participants were shown a series of paired stimulus-response magnitudes where the relationship between these 2 dimensions conformed to a cyclic function. Participants were shown to extrapolate from these training data in a nonmonotonic way, contrary to predictions from EXAM. A new model of ...
Understanding how people generalize and extrapolate from limited amounts of data remains an outstand...
Statistical learning refers to our sensitivity to the distributional properties of our environment. ...
People are capable of learning diverse functional relationships from data; nevertheless, they are mo...
This article reports the results of an experiment addressing extrapolation in function learning, in ...
Understanding the development of non-linear processes such as economic or population growth is an im...
We introduce a new approach for exploring how humans learn and represent functional relationships ba...
This paper serves to compare existing models of function learning (EXAM & POLE) on a complex int...
E. L. DeLosh, J. R. Busemeyer, and M. A. McDaniel (1997) found that when learning a positive, linear...
We oftenen counter pairs of variables in the world whose mutual relationship can be described by a f...
We often encounter pairs of variables in the world whose mutual relationship can be described by a f...
We often encounter pairs of variables in the world whose mutual relationship can be described by a f...
To give an adequate explanation of cognition and perform certain practical tasks connectionist syste...
Investigation of concept learning has focused predominantly on categorization, in which stimuli are ...
Many events that humans and other organisms experience contain regularities in which certain element...
Accounts of how people learn functional relationships between continuous vari-ables have tended to f...
Understanding how people generalize and extrapolate from limited amounts of data remains an outstand...
Statistical learning refers to our sensitivity to the distributional properties of our environment. ...
People are capable of learning diverse functional relationships from data; nevertheless, they are mo...
This article reports the results of an experiment addressing extrapolation in function learning, in ...
Understanding the development of non-linear processes such as economic or population growth is an im...
We introduce a new approach for exploring how humans learn and represent functional relationships ba...
This paper serves to compare existing models of function learning (EXAM & POLE) on a complex int...
E. L. DeLosh, J. R. Busemeyer, and M. A. McDaniel (1997) found that when learning a positive, linear...
We oftenen counter pairs of variables in the world whose mutual relationship can be described by a f...
We often encounter pairs of variables in the world whose mutual relationship can be described by a f...
We often encounter pairs of variables in the world whose mutual relationship can be described by a f...
To give an adequate explanation of cognition and perform certain practical tasks connectionist syste...
Investigation of concept learning has focused predominantly on categorization, in which stimuli are ...
Many events that humans and other organisms experience contain regularities in which certain element...
Accounts of how people learn functional relationships between continuous vari-ables have tended to f...
Understanding how people generalize and extrapolate from limited amounts of data remains an outstand...
Statistical learning refers to our sensitivity to the distributional properties of our environment. ...
People are capable of learning diverse functional relationships from data; nevertheless, they are mo...