Sunday, February 16, 2020

Another very simple specialist agent

A.s.a. H. learns that collisions are to be avoided since they may cause damage. Since clutter is seen to promote collisions A.s.a. evolves a specialist to clear clutter. The algorithm for this agent is very similar to that for a toy sumo robot except that the A.s.a. agent knows to give up and move on if the obstacle proves to be immovable.

Wednesday, February 12, 2020

Alternative flyer

A small quadcopter suspended from a balloon and with an instrumentation package suspended in turn below the drone. The assembly has slightly negative buoyancy. A tether can connect the instrumentation to a computer and trickle charge the drone’s battery at any time. This flyer maneuvers slowly which is an advantage for A.s.a.

Thursday, February 6, 2020


I am hacking a DSstyles sky walker drone in order to give the A.s.a. H. society of agents a small flying robot. This particular drone is encaged which greatly simplifies repeated takeoffs and landings. As a result of having an anemometer and microphone nearby A.s.a. immediately associates "flying" with "wind" and "engine noise" in its concept hierarchy. A.s.a. had already associated larger vertical motions with an atmospheric pressure decrease.

Saturday, February 1, 2020

Evolving robot explorers

The A.s.a. H. society of agents learns to specialize. One of the mobile robotic arms we have available has been used to transport some of the larger sensors; things like Geiger tubes, metal detectors, anemometers, etc. A.s.a. H. learns/creates a specialist “explorer agent” making use of these hardware components and uses it to probe previously unmapped areas.* The program this particular agent learns is relatively simple, mostly data logging and gps and/or beacon signal logging.

* Seeking out things like abundant light for solar panels, moderate temperatures, low clutter environment, etc. in order to maximize utility.