Monday, December 2, 2019

A.s.a. H.'s subconscious/unconscious

What is the subconscious (unconscious)? Everything that isn't part of current "consciousness?" Outside of short term memory?
1. Cases/patterns that are not currently activated?
2. Subsymbolic patterns?
3. reflexes?
4. pre and post processors?
5. A.s.a. H.'s core algorithms (for learning, extrapolating, interpolating, etc.)?

Sunday, December 1, 2019

Use of simulators

It is advisable to use simulators to do as much of the robotics development work as possible. John Blankenship had a nice example in the second issue of Servo Magazine this year. (Developing Robotic Behaviors)

Tuesday, November 12, 2019

Software bugs and AI

Currently there is a lot of interest in using AI to help us find and fix software bugs. On the other hand AI software may, itself, be more prone to bugs as compared to more conventional  software. If we don't fully understand what intelligence is or how it works how can we know if our AI software is buggy? There are even those who believe that human intelligence is, itself, a kludge and the resulting spaghetti code needed to model it is likely to be buggy. Most AI researchers find that it is harder to debug AI code. Its harder still to debug the software when robots are involved.

Sunday, November 10, 2019

Arduinos for A.s.a. H. and AI

Employed on the lowest layer of the A.s.a. H. hierarchy Arduinos are adequate for some light preprocessing, postprocessing (like PID control), and for simple reflexes. (Raspberry Pis are suitable for somewhat heavier computing tasks. Arduinos can be plugged into them and the Raspberry Pis used as a next higher layer. See, for example, Beginning Robotics with Raspberry Pi and Arduino, Jeff Cicolani, Apress, 2018) The Arduinos can then also do analog to digital conversions for the Raspberry Pis.

Thursday, November 7, 2019

Plasma processing

Plasma processing and plasma chemistry may benefit from the use of pulsed plasma discharges. Pulsating discharges make possible access to plasma conditions that are not attainable with conventional steady discharges. (R. Jones, Sing. J. Phys., vol. 5, page 27, 1988)

Tuesday, October 22, 2019

Levels of explanation

A.s.a. H. learns causal sequences at various different levels of abstraction in the memory hierarchy. Stephanie Ruphy explains why this may be valuable (Scientific Pluralism Reconsidered, U. Pittsburgh, 2013, especially pages 38-44.)

Monday, October 21, 2019

Lifelong machine learning

As A.s.a. H.'s casebase grows processing (thinking) will slow down unless forgetting (of less valuable cases) can be adjusted to roughly equal the rate at which new cases are learned/added. How could/should this be done?