Tags / 15 quotes from 2 sources
#connectionism
From Encyclopedia To Ontology: Toward Dynamic Representation Of The Discipline Of Philosophy
Problem: “philosophy of x” vs. “x”
In numerous places in the expert-supplied taxonomies, we also noticed that cat- egory names sometimes included a “philosophy of” prefix and sometimes did not; examples include “artificial intelligence” vs. “philosophy of artificial intelligence,” “connectionism” vs. “philosophy…
Problem: how to differentiate categories from individuals? a sep-driven approximation..
Another important aspect of ontology design concerns the drawing of a line between categories and individuals. For instance, should connectionism be considered an instance of the category philosophy of articial intelligence, or should it be treated as a subcategory with…
Introducing Artificial Intelligence (Henry Brighton and Howard Selina)
Connectionism models the mind on the brain
Connectionism gained popularity in the 1980s and is often depicted as a radical departure from the classical, symbolic approach to AI. Rather than viewing the processes of the mind as a computer program, connectionism draws a parallel between the processes of the mind and the…
Artificial neurons as activation units
The building blocks of neural networks are simplified versions of biological neurons called activation units. These units have a set of input connections and a set of output connections. These connections model the job performed by axons.
The brain computes in parallel
The brain is massively parallel, whereas most computers compute serially. This is why the brain is so fast, despite its relatively slow machinery. The property of parallelism present in neural networks makes connectionist models appealing. The manner in which they carry out the…
Machine learning spans symbols and networks
Machine Learning is a branch of AI that spans both the classical symbolic approach and connectionism. Here, models of learning capture the ability of an agent to improve itself in light of information in the environment. Often, the ability of connectionist systems to learn is…
Distributed representations
The kinds of information processing performed by neural networks can differ fundamentally in nature from those found in symbolic systems. Representations are often distributed in the same way that processing can be distributed. A distributed representation is spread out across…
Artificial neurons rarely represent anything alone
Of course, neural networks themselves are built up from atomic units – artificial neurons – but these units are rarely used by the designer to represent anything in themselves.
A property spread across many neurons
So, in a distributed representation, a single neuron is unlikely to be responsible for representing the number of legs of our candidate animal. Instead, the number of legs would be represented by a complex pattern of activity over a wide number of neurons. Some of these neurons…
You can't point at a distributed representation
As a general rule, you can’t locate specific items of information by pointing your finger at part of a distributed representation in the same way that you can with a local representation.
Searle's Chinese gym
Predictably, the resilient Searle stands firm and replies with the Chinese Gym. Instead of a room containing a lone Searle, he imagines a gym full of non-Chinese speakers, one for each neuron in the neural network.
The whole is more than its neurons
However, the Chinese Gym does serve as an illustration that the whole can be more than the sum of the parts. In a sub-symbolic system, the atomic units, neurons and their structured relationship to other neurons, do not individually do much at all. Only when the collection is…
Connectionism as a way to ground symbols
Harnard views connectionism as a good candidate for achieving this grounding, especially when coupled with a symbolic system.
Breaking the circle of meaningless symbols
How can symbols ever be grounded by anything but other meaningless symbols? Part of the problem of ascribing meaning to a symbol requires that the circle of meaninglessness be broken. Harnard imagines a classical symbolic system sitting on top of a sub-symbolic connectionist…
Hybrid systems escape Searle's closed world of symbols
It is the connectionist system that supplies the sensory images. By combining symbolic and connectionist systems, Harnard believes we can begin to break out of the closed world of meaningless symbols that Searle discusses.