The Application of Artificial Intelligence in Cognitive Psychology Cognitive psychology seeks to comprehend the complexities of cognition by doing research, testing, and developing models of how the human mind handles and processes complicated information during attention, memory, and perception (Zivony, 2019). In addition to studying how people think, cognitive psychologists try to build systems that think like people do. They aim to create machines that can understand and take actions in the world just like humans can. Cognitive psychologists use psychological theories as a guide to develop their computer programs. For example, researchers may want to build a program that behaves like a person would if they were trying to decide what to eat for lunch. They might first ask themselves what kinds of foods they like and then use that information to select from among several options. At each step of this process, different parts of the brain are activated. By recording the patterns of neural activity triggered by various tasks, scientists hope to one day be able to build computers that function using similar brain mechanisms.
In recent years, cognitive psychologists have started applying their knowledge of human thought to building intelligent machines. They believe that being able to simulate how people's brains work will allow them to design computer programs that behave like people do. For example, a cognitive psychologist could use her understanding of how people make decisions to build a robot that seems like it is thinking about its choices before making ones like people do. Or she could build a machine that learns from experience much like people do.
Furthermore, cognitive science is a scientific study of human thinking, emotions, language, perception, attention, and memory that is multidisciplinary in nature. However, the goal of artificial intelligence (AI) is to investigate the architecture of computers and software capable of intelligent behavior. Cognitive scientists study brains as well as computer systems and try to explain how they work.
Cognitive science has had an important impact on the development of AI. Before 1980, most research in AI was done by psychologists and neuroscientists who tried to apply their knowledge about animal behavior and brain function to building intelligent machines. This approach was called "symbolic" because it used symbols such as words or sentences to represent concepts. In 1980, Frank Rosenblatt organized a meeting at MIT called the "Conferences on Artificial Intelligence and Psychology". The aim of this meeting was to bring together researchers from both fields to discuss how their different but related perspectives could be used to build more intelligent machines. As a result, cognitive psychology began to influence the design of new algorithms and architectures that are now used in many popular AI applications. For example, when trying to understand what someone says in text form, modern linguists often turn to psycholinguistics, the study of human thought processes while reading and writing.
Since then, cognitive scientists have continued to explore how people think and act, which has led to new insights being made into how computers can do the same.
The purpose of these AI Notes PDF is to introduce intelligent agents and reasoning, heuristic search strategies, game playing, knowledge representation, and reasoning with uncertain knowledge. Cognitive Science, Thought Laws, Turing Test, Rational Agent.
Cognitive psychologists used the concept of information processing as a model of how human cognition works. The eye, for example, takes visual information and converts it into electric neuronal activity, which is then transmitted back to the brain, where it is "stored" and "coded." Cognitive psychologists claim that this is how humans think: They also convert incoming information into "mental representations," which are encoded in memory. These mental representations are later retrieved when needed for decision-making or action.
Here is an example of information processing: When reading this sentence, you first decode the letters on the page into their corresponding sounds (decoding). You then analyze these sounds (analyzing) to understand their meaning (interpretation). Finally, you encode what you have interpreted into long-term memory (encoding). Decoding, analyzing, and encoding are all steps in the process of information conversion.
After thinking about the question, they may come up with some factors they believe are important in choosing a city - such as quality of cheese and price. These factors would be converted into a set of questions - for example, "which cities have good cheese and low prices?" - and then checked against a list of candidates. This series of actions constitutes one step in the process of information conversion.