TY - JOUR
T1 - Tasks for aligning human and machine planning
AU - van Opheusden, Bas
AU - Ma, Wei Ji
N1 - Funding Information:
This work was supported by grants IIS-1344256 from the National Science Foundation and R01MH118925-01 from the National Institutes of Health .
Publisher Copyright:
© 2019
PY - 2019/10
Y1 - 2019/10
N2 - Research on artificial intelligence and research on human intelligence rely on similar conceptual foundations and have long inspired each other [1,2•]. However, achieving concrete synergy has been difficult, with one obstacle being a lack of alignment of the tasks used in both fields. Artificial intelligence research has traditionally focused on tasks that are challenging to solve, often using human performance as a benchmark to surpass [3–7]. By contrast, cognitive science and psychology have moved towards tasks that are simple enough to allow for detailed computational modeling of people's choices. These divergent objectives have led to a divide in the complexity of tasks studied, both in perception and cognition.
AB - Research on artificial intelligence and research on human intelligence rely on similar conceptual foundations and have long inspired each other [1,2•]. However, achieving concrete synergy has been difficult, with one obstacle being a lack of alignment of the tasks used in both fields. Artificial intelligence research has traditionally focused on tasks that are challenging to solve, often using human performance as a benchmark to surpass [3–7]. By contrast, cognitive science and psychology have moved towards tasks that are simple enough to allow for detailed computational modeling of people's choices. These divergent objectives have led to a divide in the complexity of tasks studied, both in perception and cognition.
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U2 - 10.1016/j.cobeha.2019.07.002
DO - 10.1016/j.cobeha.2019.07.002
M3 - Review article
AN - SCOPUS:85071454656
SN - 2352-1546
VL - 29
SP - 127
EP - 133
JO - Current Opinion in Behavioral Sciences
JF - Current Opinion in Behavioral Sciences
ER -