Discrete statements are used in programming languages. So a symbol (a symbol phrase or sentence) can be used to represent both data and programming actions. Discrete Reasoning might be compared to something that has the potential to be more like an algorithm. (Of course, operational statements may be retained as data which can be run when needed) For an example of the value of Discrete Methods, let's suppose someone wanted more control over a neural network. Trying to look for logic in a neural network does not really make all that much sense if you want to find relationships between actions on the net and output. Using Discrete Methods makes a lot of sense. You might want to try fiddling with the weights of some of the nodes as the nn is running. If certain effects can be described (or sensed by some algorithm) then describing what was done and what effects were observed would be the next step in the research. Researchers are not usually able to start with detailed knowledge of exactly what is going on. So they need to start with descriptions of some actions they took and of what effects were observed. If these actions and effects can be categorized in some way then the chance that more effective observations will be obtained will increase. Jim Bromer
On Tue, Jun 19, 2018 at 11:12 PM, Mike Archbold via AGI <[email protected]> wrote: > It sounds like you need both for AI, certainly there is always a place > for logic. What's "discrete reasoning"? > > On 6/18/18, Jim Bromer via AGI <[email protected]> wrote: >> I am wondering about how Discrete Reasoning is different than Logic. I >> assume that Discrete Reasoning could be described, modelled or >> represented by Logic, but as a more practical method, logic would be a >> tool to use with Discrete Reasoning rather than as a representational >> substrate. >> >> Discrete Reasons and Discrete Reasoning can have meaning over and >> above the True False values of Logic (and the True False Relationships >> between combinations of Propositions.) >> >> Discrete Reasoning can have combinations that do not have a meaning or >> which do not have a clear meaning. This is one of the most important >> distinctions. >> >> It can be used in various combinations of hierarchies and/or in >> non-hierarchies. >> >> It can, for the most part, be used more freely with other modelling >> methods. >> >> Discrete Reasoning may be Context Sensitive in ways that produce >> ambiguities, both useful and confusing. >> >> Discrete Reasoning can be Active. So a statement about some subject >> might, for one example, suggest that you should change your thinking >> about (or representation of) the subject in a way that goes beyond >> some explicit propositional description about some object. >> >> You may be able to show that Logic can be used in a way to allow for >> all these effects, but I believe that there is a strong argument for >> focusing on Discrete Reasoning, as opposed to Logic, when you are >> working directly on AI. >> >> Jim Bromer ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Tcc2adcdd20e1add4-M3cdae40cb7794cfc8a3adf91 Delivery options: https://agi.topicbox.com/groups
