Lukasz,
Your post below was great. Your clippings from Google confirm much of the understanding that Abram Demski was helping me reach yesterday. In one of his posts Abram was discussing my prior statement that top-down activation could be either forward or backward chaining. He said "If the network is passing down an expectation based on other data, informing the lower network of what to expect, then this is forward chaining. But if the signal is not an expectation, but more like a query "pay attention to data that might conform/contradict this hypothesis, and notify me ASAP" then it is backwards chaining. And it seems realistic that it can be both of these. I am interpreting this quoted statement as implying the purpose of backward chaining is to search for forward chaining paths that either confirm or contradict a pattern of interest or that provide a path or plan to a desired goal. In this view the backward part of backward chaining provides no changes in probability, only changes in attention, and it is only the forward chaining that is found by such backward chaining that changes probabilities. Am I correct in this interpretation of what Abram said, and is that interpretation included in what your Google clippings indicate is the generally understood meaning of the term backward chaining. Ed Porter P.S. I would appreciate answers for Abram or any else on this list who understands the question and has some knowledge on the subject. -----Original Message----- From: Lukasz Stafiniak [mailto:[EMAIL PROTECTED] Sent: Tuesday, July 15, 2008 3:05 AM To: agi@v2.listbox.com Subject: Re: FW: [agi] WHAT PORTION OF CORTICAL PROCESSES ARE BOUND BY "THE BINDING PROBLEM"? On Tue, Jul 15, 2008 at 8:01 AM, Brad Paulsen <[EMAIL PROTECTED]> wrote: > > The terms "forward-chaining" and "backward-chaining" when used to refer to > reasoning strategies have absolutely nothing to do with temporal > dependencies or levels of reasoning. These two terms refer simply, and > only, to the algorithms used to evaluate "if/then" rules in a rule base > (RB). In the FWC algorithm, the "if" part is evaluated and, if TRUE, the > "then" part is added to the FWC engine's output. In the BWC algorithm, the > "then" part is evaluated and, if TRUE, the "if" part is added to the BWC > engine's output. It is rare, but some systems use both FWC and BWC. > > That's it. Period. No other denotations or connotations apply. > Curiously, the definition put by Abram Demski is the only one I've been aware of until yesterday (I believe it's the one used among theorem proving people). Let's see what googling says on "forward chaining": 1. (Wikipedia) 2. http://www.amzi.com/ExpertSystemsInProlog/05forward.htm "A large number of expert systems require the use of forward chaining, or data driven inference. [...] Data driven expert systems are different from the goal driven, or backward chaining systems seen in the previous chapters. The goal driven approach is practical when there are a reasonable number of possible final answers, as in the case of a diagnostic or identification system. The system methodically tries to prove or disprove each possible answer, gathering the needed information as it goes. The data driven approach is practical when combinatorial explosion creates a seemingly infinite number of possible right answers, such as possible configurations of a machine." 3. http://ai.eecs.umich.edu/cogarch0/common/prop/chain.html "Forward-chaining implies that upon assertion of new knowledge, all relevant inductive and deductive rules are fired exhaustively, effectively making all knowledge about the current state explicit within the state. Forward chaining may be regarded as progress from a known state (the original knowledge) towards a goal state(s). Backward-chaining by an architecture means that no rules are fired upon assertion of new knowledge. When an unknown predicate about a known piece of knowledge is detected in an operator's condition list, all rules relevant to the knowledge in question are fired until the question is answered or until quiescence. Thus, backward chaining systems normally work from a goal state back to the original state." 4. http://www.ontotext.com/inference/reasoning_strategies.html " * Forward-chaining: to start from the known facts and to perform the inference in an inductive fashion. This kind of reasoning can have diverse objectives, for instance: to compute the inferred closure; to answer a particular query; to infer a particular sort of knowledge (e.g. the class taxonomy); etc. * Backward-chaining: to start from a particular fact or from a query and by means of using deductive reasoning to try to verify that fact or to obtain all possible results of the query. Typically, the reasoner decomposes the fact into simpler facts that can be found in the knowledge base or transforms it into alternative facts that can be proven applying further recursive transformations. 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