| QUERY | Results | Notes |
|---|---|---|
| logic programming, constraint satisfaction, constraint programming, swi prolog |
|
same pattern for logic programming and swi prolog |
| comparisons of implementations |
|
swi prolog leadds the race |
| variants of computer languages |
|
the concept is clear
Erlang has a significant propularity |
| critère | Attendu | Remarque | Réel |
|---|---|---|---|
| readability | compact foirmalism for complex problems |
programs unreadable, except the one who wrote them.
programs with with unsufficient documentation links between model and reality not always clear ('representations are poorly documented) |
|
| simplicity | |||
| efficiency | |||
| dialog with user | |||
| generality of use | logic should solve all problems |
fuzzy prologs ?
speed ? NN base systems more efficient ? |
need of fuzzy logic
need to evaluate solutions with a avlue to be optimized need of functional or imperative programing |
| natural language | produce texts for explanations | modèles avec des RN plus souples ? | toujours un sujet plutôt absent, peut-être par manque de systèmes capables de raisonner de façon non triviale. |
| learning | in opposition with hand-written rules |
well understood in simple cases
but not in complex ones
impact on the cost of the computing is often not measured. |
|
| integration with other algorithmic processes |
| Nom | Outil | Lien | Info | notes |
|---|---|---|---|---|
| Pedro Domingos | Alchemy | https:\\alchemy.cs.washington.edu\\ |
software package providing a series of algorithms for statistical relational learning and probabilistic logic inference, based on the Markov logic representation. Alchemy allows you to easily develop a wide range of AI applications, including:
|
|
| Jason Eisner | Dyna | https:\\dyna.readthedocs.io\\en\\latest\\ | Dyna is an new declarative programming language developed at Johns Hopkins University. | logic + solver |
| ProbLog2 was developed in the DTAI group of KULeuven, | Problog | https:\\dtai.cs.kuleuven.be\\problog\\ | Probabilistic logic programs are logic programs in which some of the facts are annotated with probabilities. ProbLog is a tool that allows you to intuitively build programs that do not only encode complex interactions between a large sets of heterogenous components but also the inherent uncertainties that are present in real-life situations. | tutorial |
| ProbLog2 was developed in the DTAI group of KULeuven, | DeepProbLog | https:\\github.com\\ML-KULeuven\\deepproblog |
DeepProbLog is an extension of ProbLog
that integrates Probabilistic Logic Programming with deep learning by introducing the neural predicate. The neural predicate represents probabilistic facts whose probabilites are parameterized by neural networks. For more information, consult the papers listed below. |
en python
besoin de
|
| Exemple | notes |
|---|---|
| Jupyter | does it work nicely really ? |