https://studiegids.vu.nl/en/courses/2024-2025/XB_0024The course has the following topic and goals. 1. Agents and Multi-Agent Systems Agent, multi-agent system, cognitive state, beliefs, actions, communication, coordination. The student is able to define the elementary concepts, and to apply their relevant aspects in the design of programs. (Applying knowledge and understanding) 2. Agent-Environment Interaction Action, percept. The student is capable of analyzing the environment in which the agent operates, and to identify the actions and relevant percepts that are available. The student is able to use the classification, actions and percepts as the basis for the design of an agent. (Applying knowledge and understanding) 3. Agent and Multi-Agent Program Action rules, modules, MAS file, launch rules. The student is able to describe the relevant programming constructs. In addition, the student is able to apply the constructs to write a multi-agent and agent programs. (Applying knowledge and understanding) 4. Basic Concepts Prolog Facts, rules, clause, queries, rule-based reasoning. The student is able to define the basic concepts in Prolog and describe the relationship between these concepts. Based on these concepts the student is able to solve simple problems in Prolog. (Applying knowledge and understanding) (Making judgements) 5. Prolog Programming Negation as failure, cut, recursion, lists. The student is able to apply constructs and these techniques to write a Prolog program. The student is able to solve problems by using a combination of negation as failure, recursion and the use of lists. In particular, the student is able to implement some search algorithms in Prolog. (Applying knowledge and understanding) 6. Reasoning in Logic Programming Unification, backtracking, depth-first search, linear search, backward chaining. The student is able to explain the computational model of logic and reasoning in Prolog and to use these concepts. Simple tasks with unification of terms can be made by the student. The student is able to construct a derivation of a unification (resolution). (Applying knowledge and understanding) (Communication) 7. Develop a MAS The student is able to build a relatively simple multi-agent system. Concepts relating to systems of rational agents are introduced to make complex decisions. (Applying knowledge and understanding) (Lifelong learning skills)AI (Artificial Intelligence) techniques that are discussed in this course are knowledge representation and reasoning techniques, and multi-agent technology. Students are taught how to develop a multi-agent system that uses knowledge representation to reason about the environment in which the multi-agent system operates.Lectures, lab sessions (with computer/ laptops). Attendance at labs is obligatory.The course is assessed through an exam and a practical part. The final grade is a weighted average of the individual exam grade (75%) and the grade of the practical part (25%). Practical part: Students get 3x a practical assignment that must be made in pairs. The assignments are graded with a mark. The grade for the practical part is the average of the marks for the assignments. There must be a minimum of 5 on average obtained for the assignments to pass the practical part. The exam consists of open or multiple-choice questions about all the material of the course. To pass the exam the grade must be at least a 5. Both the practical part and exam must at least be a 5 but the final grade should minimally be a 5.5 to pass the course. There will be a fourth bonus assignment that can be completed for a full bonus point on the course end grade. There is no second chance for the practical assignments.Materials: Slides. Learn Prolog Now! (Blackburn et al.). A cognitiveagent programming guide. (all available online)Bachelor Artificial Intelligence Bachelor Business Anatlytics