As stated here, Rule-based Reasoning systems are considered to be "old style" AI that uses rules prepared by humans - as opposed to Neural Networks where machine recognizes pattern i.e. acquires new knowledge and takes decision based upon that.
What I understand about Case-based Reasoning (CBR), it looks at the new cases in light of similar past cases, finds suitable reference cases, evaluates their application on the new case and revises it accordingly, applies it on the new case, and finally stores the case and solution as newly acquired knowledge.
Considering this, can I state that Case-based Reasoning should be considered as "new style" AI? Or is there a gap in my understanding?
I wanted to add: If anyone can offer a rough spectrum, that puts different AI approaches on different points depending on how independently they can take decision or how much prone they are to learn from experience (i.e. train their mind) instead of being 'pre-configured', that will also be welcome.