
Ask HN: Alternative/Abandoned methods for AI? - z3phyr
We have come a long way by Statistical methods. Last night, I went into a rabbit hole of Cognitive Architectures like ACT-R[http:&#x2F;&#x2F;act-r.psy.cmu.edu&#x2F;] and OpenCog[https:&#x2F;&#x2F;wiki.opencog.org&#x2F;w&#x2F;The_Open_Cognition_Project]. The intro ofcourse was not as documentation friendly as the width of excellent docs on Deep Learning.<p>Are the Symbolic methods abandoned because they are proven to not work? Also, are any new researchers working on this?
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sharemywin
Here's some decision tree learners that were pretty cool at the time.

Decision tree learning is the construction of a decision tree from class-
labeled training tuples. A decision tree is a flow-chart-like structure, where
each internal (non-leaf) node denotes a test on an attribute, each branch
represents the outcome of a test, and each leaf (or terminal) node holds a
class label. The topmost node in a tree is the root node.

There are many specific decision-tree algorithms. Notable ones include:

ID3 (Iterative Dichotomiser 3) C4.5 (successor of ID3) CART (Classification
And Regression Tree) CHAID (CHi-squared Automatic Interaction Detector).
Performs multi-level splits when computing classification trees.[11] MARS:
extends decision trees to handle numerical data better. Conditional Inference
Trees. Statistics-based approach that uses non-parametric tests as splitting
criteria, corrected for multiple testing to avoid overfitting. This approach
results in unbiased predictor selection and does not require pruning.[12][13]
ID3 and CART were invented independently at around the same time (between 1970
and 1980)[citation needed], yet follow a similar approach for learning a
decision tree from training tuples.

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sharemywin
Soar had some success in the past.

TacAirSoar
[https://www.isi.edu/soar/ifor/agent/](https://www.isi.edu/soar/ifor/agent/)

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sharemywin
Here's a whole list of them.

[https://arxiv.org/pdf/1610.08602.pdf](https://arxiv.org/pdf/1610.08602.pdf)

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w_t_payne
Doug Lenat never gave up. ([https://www.cyc.com/](https://www.cyc.com/))

