Artificial Intelligence By Michelle Witcofsky And Evan Flanagan.

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Presentation transcript:

Artificial Intelligence By Michelle Witcofsky And Evan Flanagan

Definition The science that automates intelligent behaviors. It is a system that thinks and acts like humans, as in rationally and intelligently. It is the study of mental faculties through the use of computational methods. The use of computers is to do symbolic reasoning, pattern recognition, learning, and some forms of inference.

Intelligence and Machines Agents: devices that respond to stimuli from their environment Most agents have sensors that receive data Also have actuators that affect their environment Goal of A.I.: To build agents that act intelligently Two types of knowledge: Procedural knowledge – learning “how” Declarative knowledge – learning “what”

Performance v. Simulation 2 different approaches to research Performance oriented develop A.I. to enhance performance Simulation oriented develop A.I. to mimic how humans respond in certain situations Turing Test to determine difference between human or machine response

Understanding Images Weak A.I.: belief that machines can be programmed to exhibit intelligent behavior (accepted by a wide audience) Strong A.I.: belief that machines can be programmed to possess intelligence, and even consciousness; widely debated because they are internal human characteristics that cannot be identified directly

Reasoning Production Systems (1) Collection of states – where states are situations that might occur in runtime (2) Collection of productions – rules or moves of operation that are used to produce results during runtime (3) Control system – logic that solves the problem of moving from start to finish, or goal state

Artificial Neural Networks Basic properties Processing units – like neurons in organisms that transmit brain messages Output of 1 or 0, combinations of outputs to create more complicated messages Idea of inhibiting or exciting output mechanisms

Associative Memory Retrieval of information associated with the information being used in a situation Constructing machines with this has been a research goal for many years; could lead to highly developed A.I. One of the main principles of the idea of Artificial Intelligence

Genetic Algorithms Key concept in Artificial Neural Networking Research area that seeks to apply understanding of natural evolution to the task of solving a problem The trick is making a computer’s problem- solving algorithm mirror that of how we do it as humans

Evolutionary Programming Main part of creating genetic algorithms Developing programs by allowing them to evolve on their own, i.e., not just explicitly typing everything necessary for the program to run Computer/compiler makes inferences about what should be done in a given situation that is not explained in the code -field is still in its infancy -only obtained in very basic examples

Other Areas of Research Language Processing: –Requires several levels of analysis –Syntactic Analysis: breaks sentences down into parts of speech, subject/clause, etc –Semantic Analysis: identifies tone and meaning the role of each word brings to a sentence –Contextual Analysis: Brought into understanding process, an understanding of what is actually meant by the text.

Other Areas of Research Information Retrieval/Extraction: The goal of Language Processing is to allow a machine to interpret a block of text by isolating the commands it contains, thus understanding what the user wants it to do –Example: We write “emacs prog.c &” to open a file in Linux, but what if the computer could understand us saying “Open prog.c in the emacs editing program.” The machine’s ability to extract a command from that sentence is a specific goal in Artificial Intelligence

Other Areas of Research Robotics –Aimed directly at creating machines that behave intelligently –Main focus of pop- culture view on Artificial Intelligence –Most recognizable symbol of A.I. research

Other Areas of Research Database Systems –Knowing when to apply certain shared information –Like a catalog of useful data, not unlike the function of the human brain, and also the intelligence to know which data is applicable in a given situation without being told in code –“closed-world database” – contains all true facts relating to a certain topic

Other Areas of Research Expert Systems –Software packages designed to assist in certain situations when an expert is required –Perfect for systems that work for specific areas – can hold all usable information for a specific function or job –Often organized as a collection of rules or facts that are relevant in the given situation

Considering the Consequences Great potential to benefit –Helping mankind solve hard problems we struggle with However, also great potential to be harmful –Challenging human intellect –Altering the image of humanity –Perhaps even surpassing humanity in intelligence –Focus of motion pictures like “The Matrix” trilogy and “I, Robot”