|Website:||website containing additional information|
|Period:||period 2 (week 46 through 5, i.e., 12-11-2018 through 1-2-2019; retake week 16)
|Participants:||up till now 74 subscriptions|
|Schedule:||Official schedule representation can be found in Osiris|
|week: 5||Thu 31-1-2019||8.30-11.30 uur||room: OLYMPOS-HAL2|
|week: 16||Mon 15-4-2019||13.30-16.30 uur||room: -||retake exam|
|Note:||No up-to-date course description available.|
Text below is from year 2017/2018
|Contents:||This course is about the theory of so-called intelligent agents, pieces of software that display some degree of autonomy, realised by incorporating `high-level cognitive / mental attitudes' into the modelling of this kind of software. These mental attitudes comprise 'informational' and 'motivational' ones and are often of the so-called BDI kind, dealing with 'beliefs', 'desires' and 'intentions' of agents. The agent concept calls for an integration of several topics in artificial intelligence, such as knowledge representation and reasoning (in particular reasoning about action and change) and planning.
Agent technology, as the field is generally called, has a great potential of applications, ranging from intelligent personal assistants to e-commerce and robotics (where in the latter case often the term 'cognitive robotics' is used).
The course is devoted mainly to the philosophical and theoretical (mostly logical) foundations of the area of intelligent agents, both focusing on single agents and on multi-agentsystems.
Textbooks and collection of articles.
|Course form:||Lectures and exercise classes (`werkcolleges')|
|Exam form:||Written exam and presentations.
|Minimum effort to qualify for 2nd chance exam:||To qualify for the retake exam, the grade of the original must be at least 4.|
|Description:||Overview in brief:
* introduction "What are intelligent agents?"
* agent architectures
* knowledge representation, ontologies, Web Ontology Language (OWL)
* agent communication
* logical foundations of actions and single agents
* social/cognitive models of agents|