The overall research goal of artificial intelligence is to create technology that allows computers and machines to function in an intelligent manner. The general problem of simulating (or creating) intelligence has been broken down into sub-problems.
These consist of particular traits or capabilities that researchers expect an intelligent system to display. The traits described below have received the most attention.Erik Sandwell emphasizes planning and learning that is relevant and applicable to the given situation.
- Reasoning, problem solving : Early researchers developed algorithms that imitated step-by-step reasoning that humans use when they solve puzzles or make logical deductions.By the late 1980s and 1990s, AI research had developed methods for dealing with uncertain or incomplete information, employing concepts from probability and economics.For difficult problems, algorithms can require enormous computational resources—most experience a “combinatorial explosion”: the amount of memory or computer time required becomes astronomical for problems of a certain size. The search for more efficient problem-solving algorithms is a high priority.
- Knowledge representation : Knowledge representation and knowledge engineering are central to AI research. Many of the problems machines are expected to solve will require extensive knowledge about the world. Among the things that AI needs to represent are: objects, properties, categories and relations between objects; situations, events, states and time; causes and effects; knowledge about knowledge (what we know about what other people know); and many other, less well researched domains. A representation of “what exists” is an ontology: the set of objects, relations, concepts and so on that the machine knows about. The most general are called upper ontologies, which attempt to provide a foundation for all other knowledge.
- Planning : Intelligent agents must be able to set goals and achieve them. They need a way to visualize the future–a representation of the state of the world and be able to make predictions about how their actions will change it–and be able to make choices that maximize the utility (or “value”) of available choices.In classical planning problems, the agent can assume that it is the only system acting in the world, allowing the agent to be certain of the consequences of its actions.However, if the agent is not the only actor, then it requires that the agent can reason under uncertainty. This calls for an agent that can not only assess its environment and make predictions, but also evaluate its predictions and adapt based on its assessment.
- Learning : Machine learning, a fundamental concept of AI research since the field’s inception, is the study of computer algorithms that improve automatically through experience.Unsupervised learning is the ability to find patterns in a stream of input. Supervised learning includes both classification and numerical regression. Classification is used to determine what category something belongs in, after seeing a number of examples of things from several categories. Regression is the attempt to produce a function that describes the relationship between inputs and outputs and predicts how the outputs should change as the inputs change.
- Social intelligence : Affective computing is the study and development of systems that can recognize, interpret, process, and simulate human affects.It is an interdisciplinary field spanning computer sciences, psychology, and cognitive science.While the origins of the field may be traced as far back as the early philosophical inquiries into emotion, the more modern branch of computer science originated with Rosalind Picard’s 1995 paper on “affective computing”.
- Creativity : A sub-field of AI addresses creativity both theoretically (the philosophical psychological perspective) and practically (the specific implementation of systems that generate novel and useful outputs). Some related areas of computational research include Artificial Intuition and Artificial Thinking.
- General intelligence : Many researchers think that their work will eventually be incorporated into a machine with artificial general intelligence, combining all the skills mentioned above and even exceeding human ability in most or all these areas.A few believe that anthropomorphic features like artificial consciousness or an artificial brain may be required for such a project.
Reference:https://en.wikipedia.org/wiki/Artificial_intelligence#Goals
Artificial Intelligence 