Tag Archives: ontology
09 Oct Resolving a Paradox
In time and space some things are impossible, but the pen is more powerful than reality. I can draw a world in which stairs lead in crazy, mind-bending directions, and I could probably build a structure that implemented upside-down staircases to nowhere. But I could never build the cube shown here, because it violates some […]
08 Sep Gnostic Learning Model
In prior posts in this section, and periodically in other sections of my blog, I have been exploring how humans learn, and how we might replicate those processes in computer software or (less likely) hardware. The context of the learning, or knowledge acquisition, upon which I choose to focus is language learning. While knowledge acquisition is much broader, this is an […]
28 Jul Patterns in the Mind
As we look for suitable solution designs for representing the knowledge and processes we humans use to communicate, we realize that we have no idea what knowledge in the brain looks like. Further, we only have relatively vague ideas about the processes that occur in the brain as we produce and comprehend words, phrases and sentences. […]
15 Jul From Perception and Learning to Logic
Perception and Learning I am not a cognitive scientist, so all I have said in this section is based on the work of others. On the other hand, I have probably spent more time seriously studying cognition than most computer geeks, and I have tried to form my perspectives around the best of our knowledge. The […]
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, […]
23 Jun Information Transformation
Information Exchange and Transformation Knowledge does the most good when shared. Knowledge that gets lodged in one place may not be particularly useful to many people. But moving digital information from place to place has its dangers. Automating data movement can introduce security or confidentiality issues, data duplication challenges, as well as raising the specter of […]
16 Jun Genetic Cross-Pollination
Cross Pollination Many approaches exist for simulating intelligent behavior on computers. In the past, the most popular approach was to focus on developing a technique and applying it to a problem. Most basic research has focused on single paradigms and their properties. Sometimes, however, in domains where multiple approaches to problem solving are possible, some […]
10 Jun Survival of the Fittest Knowledge
Genetic Algorithms in Search I think we can safely assume that intelligent applications, including accurate language interpreters and translators, will possess large amounts of knowledge to be processed and searched. Genetic algorithms are great for searching for obscure data in massive search spaces. The mechanism for association in computers can be defined as searching, just as humans describe their […]
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 […]