Unit 5 - Chapter 15 Flashcards
Artificial Intelligence ( AI)
is the branch of computer science that explores techniques for incorporating aspects of intelligence into computer systems.
The turing test
allows a human to interrogate two entities, both hidden from the interrogator. One entity is a human and the other a machine ( a computer). The interrogator can ask the entities questions and receive their responses. The communication is carried on in some form that does not alone reveal which entity is the computer; for example, the interrogator’s questions could be typed on a keyboard and the responses printed out. If, as a result of this questioning, the interrogator is unable to determine which entity is the human and which the computer, then the computer has exhibited sufficiently human intelligence to pass the Turing test.
The turing test
allows a human to interrogate two entities, both hidden from the interrogator. One entity is a human and the other a machine ( a computer). The interrogator can ask the entities questions and receive their responses. The communication is carried on in some form that does not alone reveal which entity is the computer; for example, the interrogator’s questions could be typed on a keyboard and the responses printed out. If, as a result of this questioning, the interrogator is unable to determine which entity is the human and which the computer, then the computer has exhibited sufficiently human intelligence to pass the Turing test.
Formal language
The language of formal logic
connectionist architecture
Connectionist networks are arrangements of several neurons into a network that can be entirely described by an architecture (how the neurons are arranged and connected), a transmission function (how information flows from one neuron to another), and a learning rule (how connection weights change over time).
connectionist architecture
Connectionist networks are arrangements of several neurons into a network that can be entirely described by an architecture (how the neurons are arranged and connected), a transmission function (how information flows from one neuron to another), and a learning rule (how connection weights change over time).
Artificial Neural Networks
usually just called neural networks, can be created by simulating individual neurons in hardware and connecting them in a massively parallel network of simple devices that act somewhat like biological neurons.
Training data
Training data is labeled data used to teach AI models or machine learning algorithms to make proper decisions. For example, if you are trying to build a model for a self-driving car, the training data will include images and videos labeled to identify cars vs street signs vs people.
State-space search and graph
A state space essentially consists of a set of nodes representing each state of the problem, arcs between nodes representing the legal moves from one state to another, an initial state and a goal state. Each state space takes the form of a tree or a graph.
Swarm Intelligence
Swarm intelligence (SI) is the collective behavior of decentralized, self-organized systems, natural or artificial.[1] The concept is employed in work on artificial intelligence. Swarm intelligence (SI) is in the field of artificial intelligence (AI) and is based on the collective behavior of elements in decentralized and self-organized systems. SI has a great involvement in the field of Internet of Things (IoT) and IoT-based systems in order to logically control their operations.
Swarm Intelligence
Swarm intelligence (SI) is the collective behavior of decentralized, self-organized systems, natural or artificial.[1] The concept is employed in work on artificial intelligence. Swarm intelligence (SI) is in the field of artificial intelligence (AI) and is based on the collective behavior of elements in decentralized and self-organized systems. SI has a great involvement in the field of Internet of Things (IoT) and IoT-based systems in order to logically control their operations.
Intelligent agent
is a form of software technology that is designed to interact collaboratively with a user somewhat in the mode of a personal assistant.
Expert-system, also called rule-based systems or knowledge-based systems.
An expert system attempts to mimic the human ability to engage pertinent facts and string them together in a logical fashion to reach some conclusion.
An expert system must contain two components
A knowledge base - A set of facts about the subject matter
An inference engine - A mechanism for selecting the relevant fats and for reasoning from them in a logical way.
Explanation facility
part of the rule-based system. This allows the user to see the assertions and rules used in arriving at a conclusion as a sort of check on the path of reasoning or for the user’s own enlightenment.
