Discover a fail-proof symbolic Thomas algorithm in this paper. Explore two efficient computational algorithms for implementation in CAS like Mathematica, Macsyma, and Maple. Includes illustrative ...

Despite the fact that many symbolic and connectionist (neural net) learning algorithms are addressing the same problem of learning from classified examples, very little is known regarding their ...

Example for Symbolic Aggregate approXimation (SAX) algorithm which transforms time series into strings. Install dependencies and run with: ...

Computational-Model-for-Symbolic-Representations / GCLF-Algorithm-Example..txt Cannot retrieve latest commit at this time.

Symbolic Automata extend classical automata by using symbolic alphabets instead of finite ones. Most of the classical automata algorithms rely on the alphabet being finite, and generalizing them to ...

The silhouette algorithm developed by Canny (1988, 1993) is a general motion planning algorithm which is known to have the best complexity of all of the general and complete algorithms. The authors ...

Symbolic AI's adherents say it closely follows the logic of biological intelligence and analyzes symbols to arrive at intuitive conclusions.

The current paper is mainly devoted to construct a generalized symbolic Thomas algorithm that will never fail. Two new efficient and reliable computational algorithms are given. The algorithms are ...

Despite the fact that many symbolic and connectionist (neural net) learning algorithms are addressing the same problem of learning from classified examples, very little is known regarding their ...