Multi-Agent Systems

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Doel vak

1. Agents and Multi-Agent Systems
Agent, multi-agent system, cognitive state, beliefs, goals, actions,
communication, coordination. The student is able to define the
elementary concepts, and to apply their relevant aspects in the design
of programs. (Knowledge and understanding) (Applying knowledge and
2. Agent-Environment Interaction
Action, percept. The student is capable of analysing 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. (Knowledge and understanding) (Applying knowledge and
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
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)

Inhoud vak

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
Materials: Slides. Learn Prolog Now! (Blackburn et al.). GOAL
programming guide. (all available online)


The course is assessed through an exam and a practical part.
The final grade is a weighted average of the exam grade (75%) and the
grade of the practical part (25%).

Practical part: Students get 4x a practical assignment that must be made
in groups. 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.

There is no second chance for the practical assignments.

Algemene informatie

Vakcode XB_0024
Studiepunten 6 EC
Periode P2
Vakniveau 200
Onderwijstaal Engels
Faculteit Faculteit der Bètawetenschappen
Vakcoördinator prof. dr. K.V. Hindriks
Examinator prof. dr. K.V. Hindriks
Docenten prof. dr. K.V. Hindriks

Praktische informatie

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Werkvormen Hoorcollege, Werkgroep

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