Logical Vs.analogical or Symbolic vs. Connectionist or Neat vs. Scruffy

On the Role of Randomization in Minimizing Neural Entropy

We consider the scruffy vs. the neat approach as first proposed by Minsky. In particular, the brain has been modeled as a society of mind. At some levels, the brain clearly processes information, at least in part, using a scruffy approach (e.g., vision). At other levels, the brain clearly processes information, at least in part, using a neat approach (e.g., logical reasoning). It has been prove...

From bio-inspired vs. psycho-inspired to etho-inspired robots

Artificial intelligence has been roughly divided into two schools of thought since its beginnings, the symbolic (also known as GOFAI, neat, classical, etc.) and the subsymbolic one (connectionist, scruffy, etc.). These two approaches have also had strong influence on the robotics field. In this paper we want to present a less known one, based on Ethology, and its application to the generation o...

Implicit Learning of Serial Reaction Time Tasks: Connectionist vs. Symbolic Models

Symbolic vs. Connectionist Learning: An Experimental Comparison in a Structured Domain

ÐDuring the last two decades, the attempts of finding effective and efficient solutions to the problem of learning any kind of structured information have been splitting the scientific community. A aholy waro has been fought between the advocates of a symbolic approach to learning and the advocates of a connectionist approach. One of the most repeated claims of the symbolic party has been that ...

A Connectionist Model of Verb Subcategorization

Much of the debate on rule-based vs. connectionist models in language acquisition has focussed on the English past tense. This paper investigates a new area, the acquisition of verb subcategorization. Verbs differ in how they express their arguments or subcategorize for them. For example, “She gave him a book.” is good, but “She donated him a book.” sounds odd. The paper describes a connectioni...