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• W1489740388 abstract "A system built on a layered reflective cognitivearchitecture presents many novel and difficult software engineeringproblems. Some of these problems can be ameliorated by erecting thesystem on a substrate that implicitly supports tracing the behaviorof the system to the data and through the procedures that producedthat behavior. Good traces make the system accountable; it enablesthe analysis of success and failure, and thus enhances the abilityto learn from mistakes. This constructed substrate provides forgeneral parallelism and concurrency, while supporting the automaticcollection of audit trails for all processes, including theprocesses that analyze audit trails. My system natively supports aLisp-like language. In such a language, as in machine language, aprogram is data that can be easily manipulated by a program, makingit easier for a user or an automatic procedure to read, edit, andwrite programs as they are debugged. Constructed within thissubstrate is an implementation of the bottom four layers of anEmotion Machine cognitive architecture, including built-inreactive, learned reactive, deliberative, and reflective layers. Asimple natural language planning language is presented for thedeliberative control of a problem domain. Also, a number ofdeliberative planning algorithms are implemented in this naturalplanning language, allowing a recursive application of reflectivelyplanned control. This recursion is demonstrated in a fifthsuper-reflective layer of planned control of the reflectiveplanning layer, implying N reflective layers of planned control.Here, I build and demonstrate an example of reflective problemsolving through the use of English plans in a block buildingproblem domain. In my demonstration an AI model can learn fromexperience of success or failure. The Al not only learns aboutphysical activities but also reflectively learns about thinkingactivities, refining and learning the utility of built-inknowledge. Procedurally traced memory can be used to assign creditto those thinking processes that are responsible for the failure,facilitating learning how to better plan for these types ofproblems in the future." @default.
• W1489740388 created "2016-06-24" @default.
• W1489740388 creator A5072535701 @default.
• W1489740388 date "2013-01-01" @default.
• W1489740388 modified "2023-09-27" @default.
• W1489740388 title "A substrate for accountable layered systems" @default.
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