SOW-MKI61
Cognitive Computational Modeling of Language and Web Interaction
Course infoSchedule
Course moduleSOW-MKI61
Credits (ECTS)6
Category-
Language of instructionEnglish
Offered byRadboud University; Faculty of Social Sciences; Artificial Intelligence;
Lecturer(s)
Contactperson for the course
L.E.C. Jacques
Other course modules lecturer
Coordinator
dr. G.E. Kachergis
Other course modules lecturer
Examiner
dr. G.E. Kachergis
Other course modules lecturer
Lecturer
prof. dr. ir. J.H.P. Kwisthout
Other course modules lecturer
Academic year2017
Period
PER3-PER4  (05/02/2018 to 13/07/2018)
Starting block
PER3
Course mode
full-time
Remarks-
Registration using OSIRISNo
Course open to students from other facultiesYes
Pre-registrationNo
Waiting listNo
Placement procedure-
Aims
  • Understand the range of problems in language and web interactions, and how AI techniques can be used to solve them.
  • Understand how these problems can be modeled as interacting cognitive processes that also help us understand behavior.
  • Understand the basic AI algorithms used to analyse general interaction data, including speech, text and clicks.
Content

Learning how to build intelligent algorithms that understand and communicate with people, and that help us understand behavior.

How do Siri and other digital assistants work? Do you love or hate autocorrect - can you do better? What can be discovered about you from your inbox, or just your browsing behavior? How does Facebook recommend news articles to you - and how would you want them to, in a perfect world. Language and Communication Technology lies at the basis of innumerable innovations in our society and has already provided remarkable new platforms (e.g. Facebook, Reddit, Etsy) and products (e.g. Amazon Echo and Cortana), and is poised for potentially greater impact - if we can develop machines with more thorough, reliable language understanding. Communication can be in spoken or written natural language (Siri or chatbots), extraction and filtering of information (e.g., tweet sentiment detection, epidemic monitoring, ad article recommendations or summarization), as well as via simpler behaviors such as sequences of clicks in a game or on a website.

In this course we study how to apply cognitively-inspired AI techniques in the broad field of communication and interaction between multiple intelligent agents (natural, or artificial, or both) with a particular focus on language. We consider how language can arise and evolve in communities of intelligent agents and how an understanding of language and communication can be used to improve the interactions between intelligent agents. In this course you will learn the psychology of human language and communication and how computers can be used to model and understand this type of interaction data, be it textual, spoken, tweets or clicks.

Levels
AI_MA

Test information
Written end of term exam and practical assignments

- Individual presentation: 10%
- Project presentation: 10%
- Written end of term project: 50%
- Practical assignments: 20%
- Discussion and participation: 10%

Prerequisites
BSc Artificial Intelligence or Computer Science (other: such as Sociology/Psychology: contact the course coordinator).

Contact information
Dr. George Kachergis; E: g.kachergis@donders.ru.nl; T: 024-361 2768

Recommended materials
Blackboard
When the course begins relevant literature/papers will be posted on blackboard.

Instructional modes
Computational assignments

Lecture

General
Weekly lecture sessions

Practical sessions

Tests
Exam
Test weight1
OpportunitiesBlock PER4, Block PER4