Representing Time (Temporal Logic)
by Peter Chapman
I have decided that time should be part of the base instruction set or innate knowledge of the A.I. engine. I am going with a straightforward theory of time that time flows inexorably forward, and that events are associated with either points or intervals in time, as on a timeline and familiar temporal logic of past, present and future. Theoretical physicists will be disappointed that I will skip other exotic models for now , such as time is an emergent phenomenon that is a side effect of quantum entanglement for instance.
Back to the problem at hand. Language is filled with verb tenses to describe time as the following:
I arrived in Boston.
I am arriving in Boston.
I will arrive in Boston.
Each describe the same action, but with different periods in time and all relative to “now”. Much of time is described relative to other events with the a most common of events: “now” and rarely described exactly as with a watch. This is another area for fuzzy logic (to be described in a future post). I will be working on this over the weekend.
Random thoughts about strong A.I. 
There is strong evidence for this idea of the fuzziness of time in relation to logic when you look at the human brain. Your brain records each moment as your experience it in very high definition (this is called sensory memory). It fades very quickly (in less than 30 seconds) unless some other reinforcement is provided to send that sensory memory to your short term memory, and as that short term memory is repeatedly used it transitions into something we would call long term memory, though the boundaries between these different memories are fuzzy themselves, there is significant evidence biologically to suggest that both, time is a relevance filter, and that your cognitive system has a way of differentiating sensory information in the present from stored information in the past.