Tag Archives: Neuromorphic Computing
02 Aug Artificial Time
Time is omnipresent – you can’t get away from it. It is woven into everything we do and say and understand. It is an inextricable element of context. I was just speaking of how the connections in our brain develop, grow and evolve over time. Representing and handling this “temporal” element is fundamental to any […]
31 Jul Modeling Non-Random Synaptic Links
I have discussed the different meanings of “random” in “The Random Hamlet” and “That’s so Random!” in which the mathematical definition presumes there is some not yet known law that governs the phenomenon, where other definitions suggest that randomness means that the phenomenon is not governed by any law. Remember our reference to Rosenblatt’s early contributions in […]
08 Jul Playing the Slots
Frames and More You could just throw everything into the blender and see if a nice smoothie comes out. But for some cuisine and some complex processing tasks, the blender model is unsatisfactory. With neural networks and semantic networks and concept graphs, it may be best to separate things by category, choose different blender speeds, […]
01 Jul Chaos About Us
Chaos About Us Chaos is all about us. I know that for certain each time I look into my kids’ rooms. When I recall my own youth, however, it occurs to me that I had a reason for the way I organized my life. It seemed meaningful to me, and although I recall how difficult it was […]
05 Jun Intelligent Traveling Salesmen
Another Sample Problem Several specific reasoning or inference problems have provided fodder for AI textbooks and experiments. One of these is the traveling salesman problem (Get an explanation and an example applet here): Given a traveling salesman who must get to x number of cities, find the shortest route the salesman can travel to reach […]
03 Jun Distributed Knowledge Representation
Distributed KR Knowledge representation schemata may be top-down, or bottom-up. In a top-down approach, one would define an area or domain of knowledge, then list the concepts within the domain and their attributes. Behaviors within the domain are often defined by that domain, and the concepts may not be able to exist independently. This approach helps enforce a […]
02 Jun Framing Formal Logic
Formal Logic Formal logic often uses set theory. Set theory uses existential (an assertion that something applies to some members of a set) and universal (a statement that applies to all members in a set) quantifiers. Despite the utility and noncommittal correctness of existential quantifiers, set operations using existential quantifiers are weaker then those using universal quantifiers. The […]
27 May Machine Components for Intelligence
If an abacus or a log and rope can be considered intelligent machines, then we can decompose their parts, possibly rearrange them, and get different kinds of intelligent machines. I know this is an extreme example of absurd reasoning. Let’s go from the opposite direction in the complexity spectrum. Can we use the human brain and its parts as […]
26 May AI Domains and Approaches
Grouping, Classifying and Categorizing How do you solve big technical problems? Rather than selecting or inventing an approach and then attempting to apply it to a problem to see how well it works, let’s analyze the problem and see if we can find or invent a solution that matches the problem space, and see if […]
20 May Cybernetic Modeling for Smarty-Pants
Introduction Model railroads come in several scales: O, HO and N gauge enable hobbyists to model real-world objects in miniature using successively smaller standards. In N gauge it is possible to build an entire city in the basement. A good model photographed with still or motion pictures may be so realistic that viewers believe they are looking […]