Friday, October 24, 2014

A danger in religion

If you believe in souls and life after death you may allow yourself to do things that are extremely dangerous for you and for society.

Wednesday, October 22, 2014


I have taught Asa H 2.0 to count (small numbers).

Vector values

In Asa H 2.0 light I typically use pattern length and frequency of pattern occurrence as components of a  case's vector value/utility. (see my blog of 19 Feb. 2011) A pattern's complexity can also be used in measuring its importance.  It is not clear which measure of complexity to use, however, permutation entropy? (Brandt and Pompe, Phys. Rev. Lett., 11 April 2002) Ke and Tong's measure? (Phys. Rev. E, 2008) or what?

Diversity in a society of Asa agents

The various agents can be trained in a wide variety of specialties.  The agents may have different values; one agent may value lifespan more than offspring.  Another agent may value offspring more than lifespan.  One knowledgebase may contain cases that value case length or complexity more.  Another knowledgebase may contain cases that value frequency of pattern recurrence more.  Such diversity will help the society deal with complex time varying environments.  The society of agents will be more capable than a single agent.

Sunday, October 19, 2014

Asa's fuzzy protologic

One sort of proto-logic works by verifying if a subset of symbols is present in a certain set. (Principles of Quantum Artificial Intelligence, Andreas Wichert, World Scientific, 2014, pg 31 ).  The set is represented by a vector which is divided into sub-vectors.   Asa searches for sub-vectors in this way but it is satisfied with an approximate rather than an exact match.

Saturday, October 18, 2014

Collective leadership

Having multiple models of the world is better than having just one (see my blogs of 17 Aug. 2012 and 13 Aug. 2012).  As a consequence diverse groups make better decisions than individuals do (and I dislike traditional  managers, governors, presidents, etc.).  A society of Asa agents may outperform an individual one.

Friday, October 17, 2014

Naming robot body parts

The concepts, "touch left", "touch right", "touch front", and "touch back" have been given to a Lego NXT robot by touching sensors at those locations in association with language input of the respective terms. The more general concept of touch is then learned at the next higher level in the hierarchy.  One can similarly locate and name any number of body parts that have input sensors.  Internal organs like the battery and recharging circuit can be identified with the sensation of "charging", "high charge", and "low charge." Categories like "right" can also be learned at a higher level in the hierarchy by association of experiences with "touch right", "turn right", etc.