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02 Aug Artificial Time

Time and Space Perception

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

Random Hairdo

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 […]

28 Jul Patterns in the Mind

Learning Head

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. […]

26 Jul Parallel Distributed Pattern Processing

PDP Networks We have discussed recognition processes in the brain. Connectionism, a fundamentally implicit approach to neural modeling, was championed by the parallel distributed processing (PDP) group. PDP networks use many interconnected processing elements (PEs) that, according to the PDP Group, configure themselves to match input data with “minimum conflict or discrepancy” (Rumelhart & McClelland, 1986, Vol. 2, […]

15 Jul From Perception and Learning to Logic

Software of Thought

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 […]

07 Jul SPARQL Fireworks

Sparkler

How do you get at knowledge in conceptually structured information stores such as graphs? There are multiple ways to get data and information in broad use today. The most common is Structured Query Language (SQL) which is used as the almost universal access formalism for getting, storing and manipulating data in relational databases. An emerging standard […]

26 Jun The Semantic Web and Model Owls

Cybersphere

Standards protect us and constrain us — not like a straight-jacket protects us from ourselves, but more like a governor on the motor protects us from going crazy. Standards organizations such as the Worldwide Web Consortium (W3C) are there to coordinate between stakeholders to develop a common way of structuring things. The Object Management Group (OMG) is a […]

07 Jun Finding a Tree in the Forest

Forest Trees

Complex Search Finding the information you need can be a problem, particularly when you have to look through tons (or terabytes) of data. I recall when geocaching first became popular. The idea that a technology could create a model for an entertaining activity that connects people in unusual ways is quite diverting. Will it still be popular […]

05 Jun Intelligent Traveling Salesmen

Roadmap with Pins

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

KR Scheme Symbol

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 […]