1.0 Introduction
The brain is composed of billions of tiny neurons all combined to create a hierarchy of complex networks. Much is unknown about intelligence and our understanding and perception of intelligence is shaping the way in which we in the 21st century are creating computer based intelligent neural networks. An intelligent system is able to retract information from its environment and comprehend without prior knowledge of the information the process, reason about the relationships between variables contained in the information and learn about the process and its operating conditions without human input. A computational approach to network dynamics focuses on the networks ability to think logically, process data and react to changes in the data which can lead to future evolution of the network.
Traditional rule based computational techniques failed to meet the requirements of search, optimisation and machine learning in large biological and industrial systems and therefore had to evolve which shaped the route in which computational intelligence had taken in the 21st century. A network is said to be computationally intelligent if it can deal with low level data analysis such as small numerical data has pattern recognition components. The main emphasis on neural networks and computationally based network systems was to come up with a learning algorithm that could be used to increase the intelligence of any given system. Fuzzy Logic was first proposed by Professor Lotfi Zadeh in1969 in the University of California Berkley. He created Fuzzy Logic to define between data by using partial set membership rather than crisp set membership or non-membership. Professor Zadeh explained that people do not need precise numerical inform...
... middle of paper ...
...dimension of the prototype memories where the network stores all memories within a stable state.
3.0 Fuzzy Logic Systems: Fuzzy Neural Network
3.1 What Is Fuzzy Logic?
Fuzzy Logic is a problem solving methodology that lends itself to implementation in a range of systems and can be implemented into networks. It allows an accurate outcome based on vague, ambiguous, imprecise input information. Fuzzy Logic is mainly used for control situations although it can be used over a variety of scenarios in situation based computing making it ideal for use within Neural Networks and they require a wide range of input variations. Fuzzy Logic processes user defined rules and therefore it can be readily modified to improve network performance, it can be used to model and control nonlinear data that would beforehand be impossible model mathematically.
3.2 Crisp Sets and Fuzzy Sets
Memory is an important and active system that receives information. Memory is made up of three different stages sensory memory, short term memory, and long term memory. According to the power point presentation, sensory memory refers to short storage of memory that allows an individual to process information as it occurs. Short term memory refers to memory that is only available for a limited time. It is information that is held for seconds or sometimes even minutes. Long term memory refers to memory that is stored for a long period of time and it has an unlimited capacity with the ability to hold as much information as possible. Retrieval is key and it allows individuals to have memories. Episodic memory refers to memory for events that we
The second stage of memory processing is storage. Aronson et al. (2013) defines storage as the process by which people store the information they just acquired. Unfortunately, memories are affected by incoming information through alteration or reconstruction. This phenomenon is referred to as recon...
A complex adaptive system is entity of networks and connections. It can “learn and adapt to change over time” which can change the “structure of the system” (Clancy, Effken, Pesut, 2008). It contains twelve elements: autopoesis or self-regenerization, open exchange, participation in networks, fractals, phase transition between order and chaos, search for fitness peaks, nonlinear dynamics, sensitive dependence, attractors that limit growth, strange attractors of emergence...
The neural network is required because of the information being scanned, traded, shipped and pulled from inventory by robots and tracking systems to report to the customer as quickly as possible. We have learned examples of AI being used today such as Expert Systems, Neural Networks, Genetic Algorithms, Intelligent Agents and Virtual
This essay will firstly briefly describe the theories and important facts about the original multi-store model of memory (MSM) and the working memory model (WMM).
The traditional three-stage memory model is one of the four major memory models. Traditional three-stage memory entails three various storage boxes to keep and process data for various lengths of time (Wiley, 2000-2010). One can actually understand the way information is modified as it is encoded, stored and then later retrieved. These three courses can be defined adequately to the memory of a computer. The first stage to remembering a fraction of data is encoding. It is the process of converting data into neural signals that will be retained in memory. Furthermore, it is first getting the data into one's brain. The second stage is to store it. Storage is the function of retaining neural coded data over time. The encoded data is then stored in the brain. In computers the information is stored on a disk or hard drive that is v...
The origins of fuzzy logic based techniques can be traced in fuzzy set theory. These techniques have found mass appeal in various computational and manufacturing engineering domains. Fuzzy logic have been successfully used to solve variety of problems in system identification, signal processing and control [10]–[12]. Recently a lot of attention is being paid towards application of fuzzy logic in various software engineering processes and artifacts such as project management, quality assurance, software testing and traceability etc. A fuzzy model structure can be represented by a set of fuzzy If-Then rules [13]. It serves as a conceptual framework which works to cater to the uncertainty in the knowledge representation. Fuzzy Logic is basically a multi-valued logic that allows intermediate values to be defined between conventional evaluations like yes/no, true/false, black/white, etc. Notions like rather warm or pretty cold can be formulated mathematically and processed by computers
The traditional notion that seeks to compare human minds, with all its intricacies and biochemical functions, to that of artificially programmed digital computers, is self-defeating and it should be discredited in dialogs regarding the theory of artificial intelligence. This traditional notion is akin to comparing, in crude terms, cars and aeroplanes or ice cream and cream cheese. Human mental states are caused by various behaviours of elements in the brain, and these behaviours in are adjudged by the biochemical composition of our brains, which are responsible for our thoughts and functions. When we discuss mental states of systems it is important to distinguish between human brains and that of any natural or artificial organisms which is said to have central processing systems (i.e. brains of chimpanzees, microchips etc.). Although various similarities may exist between those systems in terms of functions and behaviourism, the intrinsic intentionality within those systems differ extensively. Although it may not be possible to prove that whether or not mental states exist at all in systems other than our own, in this paper I will strive to present arguments that a machine that computes and responds to inputs does indeed have a state of mind, but one that does not necessarily result in a form of mentality. This paper will discuss how the states and intentionality of digital computers are different from the states of human brains and yet they are indeed states of a mind resulting from various functions in their central processing systems.
In order to see how artificial intelligence plays a role on today’s society, I believe it is important to dispel any misconceptions about what artificial intelligence is. Artificial intelligence has been defined many different ways, but the commonality between all of them is that artificial intelligence theory and development of computer systems that are able to perform tasks that would normally require a human intelligence such as decision making, visual recognition, or speech recognition. However, human intelligence is a very ambiguous term. I believe there are three main attributes an artificial intelligence system has that makes it representative of human intelligence (Source 1). The first is problem solving, the ability to look ahead several steps in the decision making process and being able to choose the best solution (Source 1). The second is the representation of knowledge (Source 1). While knowledge is usually gained through experience or education, intelligent agents could very well possibly have a different form of knowledge. Access to the internet, the la...
According to the natural evolutionary rule of “survival of the fittest”, all organisms followed this rule for evolution in the past thousands of years. Mankind, who has the highest Intelligence Quotient among all organisms, also got evolution through this “survival of the fittest”; we gradually stand on the top of the pyramid of all living beings, and are even the master of the Earth. But today, we found that natural selection may be substituted at any time. In particular, science develops along with artificial intelligence — the non-organic organisms. Artificial intelligence, which is intelligence exhibited by machines, is called a breakthrough for self-realization of human. Once upon a time, artificial intelligence was just a branch of computer science, and it was the simulation of human’s
The fuzzy is basic set of rules which is based on system error and change in error which expert advice into automatic control condition for self adaptive controller. Fuzzy represents a sequence of control mechanism to adjust the effect of certain system stimulations. It reflects the expert conditions in to appropriate control design.
All of the ways that humans gain information are mimicked by computers. Humans then proceed to analyze and store the information accordingly. This is a computer's main function in today's society. Humans then take all of this information and solve problems logically. This is where things get complex.
Artificial intelligence is a concept that has been around for many years. The ancient Greeks had tales of robots, and the Chinese and Egyptian engineers made automations. However, the idea of actually trying to create a machine to perform useful reasoning could have begun with Ramon Llull in 1300 CE. After this came Gottfried Leibniz with his Calculus ratiocinator who extended the idea of the calculating machine. It was made to execute operations on ideas rather than numbers. The study of mathematical logic brought the world to Alan Turing’s theory of computation. In that, Alan stated that a machine, by changing between symbols such as “0” and “1” would be able to imitate any possible act of mathematical
Logical AI: all facts about the situation and the goals are represented in mathematical logical language and the program decides by understanding that certain actions lead to certain results and eventually the goal Search: the program examines a large number of possible actions, understands how to do this more efficiently Pattern Recognition: program makes observations, then compares to patterns Representation: facts about the world are represented in mathematical log...
Machine learning systems can be categorized according to many different criteria. We will discuss three criteria: Classification on the basis of the underlying learning strategies used, Classification on the basis of the representation of knowledge or skill acquired by the learner and Classification in terms of the application domain of the performance system for which knowledge is acquired.