Artificial Neural Networks and Connectionist Architectures

What is the core building block of connectionist architectures?

• Computers

• Physical symbols

• Artificial neural networks (ANNs)

• Turing Machines

The Physical Symbol System (PSS) Hypothesis states that the mind:

• Is like a Turing Machine

• Functions using neural networks

• Works through artificial intelligence models

• Does not compute

According to the Church-Turing Thesis, what can a Turing Machine compute?

• Only symbolic data

• Only non-computable functions

• Computable functions

• Artificial neural networks

What is the primary advantage of Artificial Neural Networks (ANNs) over Physical Symbol Systems (PSS)?

• They require explicit rule-based programs

• They can be trained to recognize patterns

• They manipulate symbols directly

• They use complex algorithms for pattern recognition

In Artificial Neural Networks (ANNs), the connection between neurons is:

• Static

• Dynamic

• Non-existent

• Symbolic

What type of connection is used in Artificial Neural Networks?

• Fixed

• Weighted

• Symbolic

• None of the above

What is Parallel Distributed Processing in the context of ANNs?

• Information processed sequentially

• Information processed in parallel across a network

• One neuron processes all information

• Information stored in a single memory unit

What does a biological neuron require to fire?

• A) A threshold of inhibitory input

• B) A sum of excitatory and inhibitory inputs

• C) Only excitatory input

• D) A single neurotransmitter input

In Artificial Neural Networks, an artificial neuron fires when:

• A) Its weight is negative

• B) The sum of its inputs exceeds a threshold

• C) It receives an input equal to 0

• D) It has an output of 0

What is the difference between a Feedforward network and a Recurrent network?

• Feedforward networks have no hidden layers

• Recurrent networks include connections between nodes in the same layer or prior units