Practical Introspection as Inspiration for AI
AI has progressed less than other fields of information technology due to a conceptual impasse. Though much effort has been employed to overcome this situation, often it has been from a restricted point-of-view e.g. philosophy alone or algorithms alone. This paper argues for (and exemplifies) an inter-disciplinary tactic for advancing the field of AI that integrates introspection with programming. The paper has two parts: The first outlines an introspective approach that has been largely overlooked and answers some of the (rather heated) arguments that have caused introspection to be sidelined. The second part offers a practical application of this approach - presented as an algorithm.
KeywordsReinforcement Learn Case Base Reasoning Middle Ground Random Action Relevant Line
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