Programplaner og emneplaner - Student
ACIT4610 Evolutionary artificial intelligence and robotics Course description
- Course name in Norwegian
- Evolutionary artificial intelligence and robotics
- Study programme
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Master's Programme in Applied Computer and Information Technology
- Weight
- 10.0 ECTS
- Year of study
- 2021/2022
- Curriculum
-
FALL 2021
- Schedule
- Programme description
- Course history
-
Introduction
This course will present complex systems (cellular automata, networks, and agent-based) modelling and programming through state-of-the-art artificial intelligence methods that take inspiration from biology (sub-symbolic and bio-inspired AI methods), such as evolutionary algorithms, neuro-evolution, artificial development, swarm intelligence, evolutionary and swarm robotics.
Required preliminary courses
No formal requirements over and above the admission requirements.
Learning outcomes
On successful completion of the course, students will get both theoretical and practical experience within complex systems and bio-inspired/sub-symbolic AI methods. In particular, students should have the following outcomes defined in terms of knowledge, skills and general competence:
Knowledge
The student:
- Has a deep understanding of complex systems modelling and analysis
- Has advanced knowledge in sub-symbolic and bio-inspired AI methods
- Has a clear understanding of key concepts in AI such as emergence, adaptation, evolution.
- Can relate concepts in artificial intelligence and biological intelligence
Skills
The student:
- Can model and analyse complex systems using cellular automata, networks and agent- based models
- Can program complex systems using bio-inspired AI methods
- Can design and implement evolutionary and swarm robotic systems
General Competence
The student:
- Has theoretical and practical understanding of complex and biologically-inspired AI methods and evolutionary robotics methods
- Can understand and discuss relevance, strength and limitations of complex and biologically inspired systems
- Is able to work in relevant research projects
Teaching and learning methods
When the students have completed and passed the compulsory courses, they can choose a relevant specialisation from among the different courses offered by the university. Alternatively, the students can suggest relevant areas of specialisation for PSYKPRA2 themselves. The learning outcomes for PSYKPRA2 are also related to the bachelor’s thesis (PSYK3900).
Course requirements
Passed the courses PSYK1100, PSYK1210, PSYK1420, PSYK1700, PSYK1610, PSYK2100, PSYK2200, PSYK2310, PSYKPRA10, PSYK2400 and PSYK2600
Assessment
After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and competence:
Knowledge
The student can
- describe the legal basis for the relevant establishment
- explain the establishment’s professional basis and how the purpose of the establishment is described
- describe how the establishment cooperates with other parties
Skills
The student can
- communicate with users, next of kin and other partners
- perform relevant work in a sound manner
- evaluate measures that have been implemented
General competence
The student
- is capable of proposing and implementing measures that promote coping or quality of life
- knows the principles for quality assurance of his/her own work
- demonstrates academic, relational and professional skills adapted to the establishment in question
Permitted exam materials and equipment
The following must have been approved before the student’s practical training can be assessed:
- Participation in teaching activities related to the chosen specialisation (min. 80%)
- Submission of planning documents for practical training
- Participation in relevant work at the practical training establishment (minimum attendance of 90%)
- Compliance with general requirements for practical training
- Compliance with general requirements for practical training
All required coursework must be approved before the student’s practical training can be assessed.
Grading scale
Assessment of practical training
Examiners
Pass/fail
Course contact person
Aktiv innsats rundt elever med skolen som samarbeidsarena vil kunne forebygge elevers uteblivelse og frafall fra skolen, og blir en ny arbeidsarena for sosialarbeidere. Forskning viser at antallet elever med ulike sosioemosjonelle vansker øker i norsk skole, og at skolen viderefører eller forsterker allerede eksisterende sosiale forskjeller. Antallet sosialarbeidere i skolen har økt, men stillingen er fortsatt ikke lovpålagt. Emnet omhandler hvordan vi med flere yrkesgruppers kompetanse samlet i skolen kan oppnå en mer inkluderende skole med plass og ivaretakelse av mangfoldet i elevmassen. Hvordan den sosialfaglige kompetansen kan implementeres på en pedagogisk arena, er nyttig kunnskap for våre studenter og for sosialarbeidere og pedagoger ansatte i skolen.