This is a NARS inspired General Machine Intelligence (GMI) system. The current implementation only implements a NAR(non-axiomatic reasoner) for NAL1-6 and NAL7-8. NAL-9 is currently only supported with a special operator.
working definition of intelligence:
solving complex and complicated problems under adaptation with insufficient knowledge and resources
is a composition of the definition of intelligence from Dr. Pei Wang paper and the definition of intelligence from Dr. Ben Goertzel.
Running the program is easy. Note that cargo test can be omitted if the unittests should be skipped.
cargo test && cargo run --release it
cargo test && cargo run --release srv
connect to server with for example netcat: nc 127.0.0.1 2039
cargo test && cargo run --release envPong3
cargo test && cargo run --release bQA nalExp/ExTimAnimalProd0.nal
cargo doc --lib
rm -f ./logX.txt && cargo test && cargo run --release nnTrain.nlp
Documentation will follow when the features(mechanisms) and implementation has settled to a "stable" state.
A paper describing novel parts will follow.
The API documentation can be created from the source code by building the documentation.
The system accepts either Narsese or commands as inputs. Commands are used to give the reasoner compute in the form of cycles. Commands also can be used to change parameters of the input/output and/or the reasoner itself. Commands also allow to invoke special functionality of the NARS+ implementation, for example for the NLP module.
See in source file NarInputFacade.rs for a list of all implemented commands.
- rust (minimum 1.36, latest stable recommended)
- python 3.X, recommended 3.5 and up
Robot examples need pybullet, install with pip install pybullet
- unification of =/> by subj
- goals
- decision making
- Q&A for temporal, ex: <(a,^x) =/> b>?
- Q&A
- unification of =/> by pred
- use of non-temporal knowledge for temporal inference halfdone
- quests