2023
Artificial Intelligence
Name: Artificial Intelligence
Code: INF13208L
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
Informatics
Teaching languages: Portuguese
Languages of tutoring support: Portuguese, English
Regime de Frequência: Presencial
Sustainable Development Goals
Learning Goals
Students should acquire skills in:
* Search techniques to problem solving, developing the ability to formulate problems as state space search problems.
* Techniques of Knowledge Representation and Reasoning in logic. This topic introduces important foundation for students pursuing studies in Artificial Intelligence, or later in their professional lives if they have to deal with applications that need to represent knowledge.
* Representation and problem solving in Planning. Formalisms for the representation of states, actions and their consequences. Planning Systems . This topic allows the application of some of the techniques acquired in the previous topics and introduces new techniques and formalisms.
* Use logic programming as a programming language to exercise the skills in program development in Prolog acquired in other course. The use of Logic Programming (Prolog) as a logical formalism (non-monotonic) for representing common sense knowledge in artificial intelligence problems.
* Search techniques to problem solving, developing the ability to formulate problems as state space search problems.
* Techniques of Knowledge Representation and Reasoning in logic. This topic introduces important foundation for students pursuing studies in Artificial Intelligence, or later in their professional lives if they have to deal with applications that need to represent knowledge.
* Representation and problem solving in Planning. Formalisms for the representation of states, actions and their consequences. Planning Systems . This topic allows the application of some of the techniques acquired in the previous topics and introduces new techniques and formalisms.
* Use logic programming as a programming language to exercise the skills in program development in Prolog acquired in other course. The use of Logic Programming (Prolog) as a logical formalism (non-monotonic) for representing common sense knowledge in artificial intelligence problems.
Contents
1 - Introduction to Artificial Intelligence
2 - State space search: Problem solving. Actions as transition states operators. Formulation of problems as state space searchs. Complexity analysis, complete and optimal algorithms
Constraint satisfaction problems: design and alternative resolution methods. Local search: Hill climbing, simulated anealing and genetic algorithms.
3 - Decision in Games Played
4 - knowledge Representation and reasoning
Description of problems in first order logic. Choice of vocabulary, construction of rules, axioms and theorems. Knowledge representation of common sense.
Representation of problems that evolve: action and change. Representation of time and change with time constraints
Formalisms for representing action and change: Situation Calculus and Event Calculus. Planning actions with these formalisms. Frame problems, qualification and ramification
5 - Planning: Strips Notation. Partial order planner
Planning with situations calculus and event calculus
2 - State space search: Problem solving. Actions as transition states operators. Formulation of problems as state space searchs. Complexity analysis, complete and optimal algorithms
Constraint satisfaction problems: design and alternative resolution methods. Local search: Hill climbing, simulated anealing and genetic algorithms.
3 - Decision in Games Played
4 - knowledge Representation and reasoning
Description of problems in first order logic. Choice of vocabulary, construction of rules, axioms and theorems. Knowledge representation of common sense.
Representation of problems that evolve: action and change. Representation of time and change with time constraints
Formalisms for representing action and change: Situation Calculus and Event Calculus. Planning actions with these formalisms. Frame problems, qualification and ramification
5 - Planning: Strips Notation. Partial order planner
Planning with situations calculus and event calculus
Teaching Methods
The subject is introduced in the lectures where some pratical problems are also discussed. In practical classes students solve some exercises proposed in the paper, in the computer they must implement some of the algorithms studied and to use them to solve some exercises. Pratical classes sessions are also used for students to solve some of the work of the course (five).
Assessment
Final evaluation
- 70% resulting from theoretical test
- 30% resulting from 5 practical assignments, 20% each
Continuous evaluation:
- 70% 2 tests during the period, 50% each
- 30% resulting from 5 practical assignments, 20% each
- 70% resulting from theoretical test
- 30% resulting from 5 practical assignments, 20% each
Continuous evaluation:
- 70% 2 tests during the period, 50% each
- 30% resulting from 5 practical assignments, 20% each
Teaching Staff
- Irene Pimenta Rodrigues [responsible]
