Artificial Intelligence

The modern definition of artificial intelligence (or AI) is "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions which maximizes its chances of success.

John McCarthy, who coined the term in 1956, defines it as "the science and engineering of making intelligent machines." Other names for the field have been proposed, such as computational intelligence, synthetic intelligence or computational rationality.

The term artificial intelligence is also used to describe a property of machines or programs: the intelligence that the system demonstrates. AI research uses tools and insights from many fields, including computer science, psychology, philosophy, neuroscience, cognitive science, linguistics, operations research, economics, control theory, probability, optimization and logic.

AI research also overlaps with tasks such as robotics, control systems, scheduling, data mining, logistics, speech recognition, facial recognition and many others. Computational intelligence Computational intelligence involves iterative development or learning (e.g., parameter tuning in connectionist systems).

Learning is based on empirical data and is associated with non-symbolic AI, scruffy AI and soft computing.

Subjects in computational intelligence as defined by IEEE Computational Intelligence Society mainly include: Neural networks: trainable systems with very strong pattern recognition capabilities. Fuzzy systems: techniques for reasoning under uncertainty, have been widely used in modern industrial and consumer product control systems; capable of working with concepts such as 'hot', 'cold', 'warm' and 'boiling'. Evolutionary computation: applies biologically inspired concepts such as populations, mutation and survival of the fittest to generate increasingly better solutions to the problem.

These methods most notably divide into evolutionary algorithms (e.g., genetic algorithms) and swarm intelligence (e.g., ant algorithms). With hybrid intelligent systems, attempts are made to combine these two groups.

Expert inference rules can be generated through neural network or production rules from statistical learning such as in ACT-R or CLARION.

It is thought that the human brain uses multiple techniques to both formulate and cross-check results.

Thus, systems integration is seen as promising and perhaps necessary for true AI, especially the integration of symbolic and connectionist models.

2.) Граматичний матеріал. Прикметник. Ступені порівняння прикметників; Прислівник. Ступені порівняння прислівників

Ознайомтесь з теоретичним матеріалом з теми.

Якісні прикметники мають три ступені порівняння:

• позитивний;

• вищий;

• найвищий.

Способи утворення ступенів порівняння

а) У односкладних (не більше двох складів) прикметників – за допомогою суфіксів.

Розгляньте таблицю односкладних прикметників та зверніть увагу на правопис.

Позитивний ступінь	Вищий ступінь	Найвищий ступінь
fine clean hot happy	finer cleaner hotter happier	(the) finest (the) cleanest (the) hottest (the) happiest

б) У багатоскладних (більше двох складів прикметників) – за допомогою додавання особливого слова.

Позитивний ступінь	Вищий ступінь	Найвищий ступінь
difficult wonderful useful	more difficult more wonderful more useful	(the) most difficult (the) most wonderful (the) most useful

в) Виключення з правил:

Позитивний ступінь	Вищий ступінь	Найвищий ступінь
good well bad many much little far old	better worse more less farther, further older, elder	(the) best (the) worst (the) most (the) least (the) farthest, (the) furthest(the) oldest, (the) eldest

1. Form degrees of comparison of the following adjectives.

Short, long, busy, poor, nice, clever, polite, pretty, shy, merry, early, sweet, talented, interesting, beautiful, unpleasant, comfortable.

2. Say what degree of comparison is used. Translate the sentences into Ukrainian.

1. The longest river in Ukraine is the Dnieper.

2. He is my best friend.

3. This text is more interesting than that one.

4. The more you learn, the better you know.

5. The nearer the winter, the colder the days.

6. Cotton is more flexible than linen.

7. Cotton fibres are smoother, stiffer and straighter than wool.

8. Fibres saturated with water are 20 per cent stronger than dry ones.

3. Open the brackets using the proper degree of comparison.

1. He was only five years (young) than I was.

2. They stopped at one of (good) hotels in town.

3. At that moment he was (happy) person in the world.

4. Please, show me (short) way to the department store.

5. I hope to read this book (fast) than that one.

6. Ann plays the piano (bad) than the other girls.

7. I have (little) time for reading than my friends has.

8. Tom is (good) student than John.

Література:

1. Барановська Т.В. Граматика англійської мови. Збірник вправ: Навч. посібник. Видання друге, виправлене та доповненею – Мова англ., укр. – Київ: ТОВ “ВП Логос-М», 2007. – 384с.

2. Л.В. Мисик, А.Л. Арцишевська, Л.Р. Кузнєцова, Л.Л. Поплавська. Англійська мова. Комунікативний аспект. / За ред. доц. Мисик Л.В. – Підручник. – К.: Атіка, 2000. – 368с.

3. Гужва Т. М. Англійська мова: Розмовні теми: Навч. посіб. Для студентів фак. iнозем. Філології, університетів, ліцеїв, гімназій та коледжів. – Харків: Фоліо, 2005. – 414с.

4. Бессонова І. В. Англійська мова (за професійним спрямуванням). Навчальний посібник для дистанційного навчання. – К.: Університет «Україна», 2005. – 263с.