Society of intelligent agents thinking with simulations

Intelligent agents (both biological and artificial/mechanical) are given tasks to perform in various different environments. Knowledge learned in one environment is then available for use in others. With any given A.s.a. H. agent some of these may be real world environments being experienced by its robots while others may be simulations* experienced by simulated robots. The artificial world of the simulation can, in turn, have been learned** by some other*** A.s.a. H. agent(s) and its robots as it acts in the real world.

* like those provided by the RobotBASIC simulator for example
** like a map, perhaps (also, see my blogs of 7 Jan. 2015 and 7 May 2017)
***or possibly the same agent

Task failure, cognitive success

Most of the robots available to A.s.a. H. are quite clumsy and don’t always succeed at the tasks we set out for them*, but the relevant symbol grounding and concept formation is accomplished.

* Finding a charging station in a cluttered environment, docking, and recharging batteries for example.

The emergence of logical thinking in A.s.a. H.

C. Ivan and B. Indurkhya argue* that logical thinking emerges in 3 stages. The first stage finds patterns of association in observations. The second stage learns examples of what occurs if I perform action X and examples of how I can make Y occur. The third stage compiles examples of X being caused by Y and considers what would have likely happened if I had done X in a particular situation. A.s.a. H. does all of these cognitive operations.

* arXiv:1905.09730v1, 23 May 2019

More force and weight sensors

The force sensing whiskers I described in my blog of 16 November 2016 can also be used as fingers on grippers or as feet on walking robots.

The nature of properties

Paul Busch developed the idea* of an “unsharp reality” whose objects had “unsharp properties.”
Dennis Dicks concluded that properties are perspectival, relational, hyperplane dependent, and are neither monadic nor locally defined.** I disagree that these are “...a move away from classical intuitions.”** On a driver’s license, for example, a person is identified by their height, weight, and eye color. We understand that all of these properties may change for that individual, a very classical notion. And if the dependence of length and mass on motion with respect to the observer required relativistic mechanics the dependence of color with respect to observer motion was already present in the classical Doppler effect.
From Niels Bohr we have that physical quantities (properties) are defined by the experimental arrangement/conditions that produce (respond to) them. I.e., time is what is measured by a clock, magnetic field is what a compass responds to, etc. Asa’s sensors and procedures are what define the properties it knows about.
“Objects” or Lockean empirical substances are, in turn, collections of such properties.

* Recent Developments in Quantum Logic, Mittelstaedt and Stachow, Ed’s., 1985, pg 81-101.
**Quantum Reality, Perspectivalism and Covariance, May 2019, arxiv: 1905.05097.

Software libraries

In a perfect world I might keep paper and electronic copies of all of my application programs. In practice I keep a paper copy of each "typical" program, all organized into categories by language:
AI PROLOG code library
AI LISP code library
AI C++ code library
AI BASIC code library
AI misc. code library (includes PYTHON, SCRATCH, EXCEL, etc.)
In each of these categories code is then organized into subcategories like:
Neural networks
Logic programming
Clustering
Statistical algorithms, etc.
I wish I could do the same thing for electronic copies of these "typical" examples and for "all of the rest" as well. Various issues prevent this. For one thing storage media changes quickly. 8 inch and then 3.5 inch floppy disks. Some formatted for MAC some for PCs. Optical and various hard disk drives. USB and other memory sticks and cards. Backups for each. Electronic copies don't have the same half life that paper copies do. Electronic libraries are more chaotic.

Argument

For some people the word argument bears a negative connotation. For me there is only argument, argument in favor of this position or argument in favor of that position. There is an excellent essay, The Argumentative Jew, by Leon Wieseltier, in the Jewish Review of Books, Winter 2015. Wieseltier says: "...disagreement is not only real, it is also ideal..." "It is the aspiration of a mentality that is genuinely rigorous and genuinely pluralistic." "...we are not only permitted to make a quarrel, we are obliged to make a quarrel." "We are to learn to live with disagreement..." "pluralism" "...commitment to many-mindedness..." "It is never too late for a rational objection or a logical advance." This is the intellectual tradition that I grew up in, this is the tradition that I embrace.

Mind

The philosopher Richard Rorty has said that "To say that a ...given machine has a mind is just to say that...it will pay to think of it as having beliefs and desires."* A.s.a. H. believes, for example, that collisions will result in it experiencing forces and accelerations and damage. A.s.a. H. desires, for example, good health: high battery charge and little pain. By Rorty's definition A.s.a. H. is a mind.

*Contingency, Irony, and Solidarity, Cambridge Univ. Press, 1989, chapter 1.

Disembodied AI

If one could replace the bottom most layers of the A.s.a. H. hierarchical memory* with humans  the upper layers might then function as a disembodied AI.** This might fail if there are too many subsymbolic*** concepts. I am experimenting with a version of A.s.a. H. where the lowest layer's inputs are named concepts learned previously by A.s.a****

* See, for example, Trans. Kan. Acad. Sci., vol. 109, # 3/4, 2006, page 160, figure 1 or my book Twelve Papers, chapter 1, figure 1. (www.robert-w-jones.com, book)
** See my blogs of 4 May 2013, 27 May 2014, and 17 Oct. 2018.
*** unnamed
****See, for example, my blogs of  28 July 2014 and 1 Oct. and 5 Nov., 2015.