Name
Abstract | ||
|---|---|---|
Cognitive biases explaining human deviation from formal logic have been broadly studied. We here try to give a step toward the general formalism still missing, introducing a probabilistic formula for causal induction. It has symmetries reflecting human cognitive biases and shows extremely high correlation with the experimental results. We apply the formula to learning or decision-theoretic tasks, n-armed bandit problems. Searching for the best cause for reward, it exhibits an optimal property breaking the usual trade-off between speed and accuracy. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-21314-4_30 | ECAL (2) |
Keywords | Field | DocType |
decision-theoretic task,best cause,formal logic,causal induction,symmetric model,general formalism,human cognitive bias,human deviation,probabilistic formula,cognitive bias,heuristics,mutual exclusivity | Cognitive bias,Computer science,Correlation,Heuristics,Artificial intelligence,Formalism (philosophy),Probabilistic logic,Cognition,Homogeneous space,Machine learning,Mutually exclusive events | Conference |
Citations | PageRank | References |
2 | 0.37 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tatsuji Takahashi | 1 | 6 | 2.90 |
| Kuratomo Oyo | 2 | 2 | 1.72 |
| Shuji Shinohara | 3 | 5 | 3.91 |