Representation (AMBR) Model Comparison Project is to advance the state of the art in cognitive modeling. It is organized as a series of model comparisons, moderated by a team from BBN Technologies. In each comparison, a challenging behavioral phenomenon is chosen for study. Data are collected from humans performing the task. Cognitive models representing different modeling architectures are created, run on the task, and then compared to the collected data. The current effort focuses on models of category learning in a dynamic, dual-task environment. Model comparisons such as this, especially with directl
Many evaluations of cognitive models rely on data that have been averaged or aggregated across all e...
We develop a model of the interaction between representation building and category learning. Our mod...
(a) Time-varying representational similarity analysis between human MEG data and the computational m...
cognitive modeling, human behavior representation, multi-tasking, HLA, concept learning ABSTRACT: Th...
The evaluation of an AGI system can take many forms. There is a long tradition in Artificial Intelli...
The evaluation of an AGI system can take many forms. There is a long tradition in Artificial Intelli...
In the field of cognitive science, the primary means of judging a model’s viability is made on the b...
The ability to learn categories and classify new items or experiences is an essential function for e...
Cognitive Science and Artificial Intelligence share compatible goals of understanding and possibly g...
How should we decide among competing explanations (models) of a cognitive phenomenon? This problem o...
Many evaluations of cognitive models rely on data that have been averaged or aggregated across all e...
We present a brief review of modern machine learning techniques and their use in models of human men...
Cognitive Science and Artificial Intelligence share compatible goals of understanding and possibly g...
We contrasted and compared independently developed computational models of human performance in a co...
Abstract. Conceptual modelling involves many higher order cognitive processes, such as relational re...
Many evaluations of cognitive models rely on data that have been averaged or aggregated across all e...
We develop a model of the interaction between representation building and category learning. Our mod...
(a) Time-varying representational similarity analysis between human MEG data and the computational m...
cognitive modeling, human behavior representation, multi-tasking, HLA, concept learning ABSTRACT: Th...
The evaluation of an AGI system can take many forms. There is a long tradition in Artificial Intelli...
The evaluation of an AGI system can take many forms. There is a long tradition in Artificial Intelli...
In the field of cognitive science, the primary means of judging a model’s viability is made on the b...
The ability to learn categories and classify new items or experiences is an essential function for e...
Cognitive Science and Artificial Intelligence share compatible goals of understanding and possibly g...
How should we decide among competing explanations (models) of a cognitive phenomenon? This problem o...
Many evaluations of cognitive models rely on data that have been averaged or aggregated across all e...
We present a brief review of modern machine learning techniques and their use in models of human men...
Cognitive Science and Artificial Intelligence share compatible goals of understanding and possibly g...
We contrasted and compared independently developed computational models of human performance in a co...
Abstract. Conceptual modelling involves many higher order cognitive processes, such as relational re...
Many evaluations of cognitive models rely on data that have been averaged or aggregated across all e...
We develop a model of the interaction between representation building and category learning. Our mod...
(a) Time-varying representational similarity analysis between human MEG data and the computational m...