SC10 Evolution of Interaction and Meaning on the Web
The Web is a global arena of online communication and computation that evolves in novel, technologically mediated ways through massive-scale human and machine interaction. This course will introduce the main fundamental techniques that can be used to model systems where interaction and meaning evolve on the web, with a focus on how we can conceptualise these processes using computationally grounded techniques. Emphasis will be given on capturing the human-centric nature of these sociotechnical systems so we can discover the principles that underpin well-designed, sustainable, and ethically sound systems.
The course will begin with an introduction to the overall topic and its challenges, proceed to relevant areas and their methods, distinguishing by techniques that focus on interaction vs. those that focus on meaning, and close with an extensive discussion of real-world case studies and their human and social dimension.
Preliminary schedule of sessions:
1. Introduction: Collective intelligence, social computation, and the Web
2. Interaction: Multiagent systems, game theory, learning
3. Meaning: Ontologies, pragmatics, grounding, language evolution
4. Examples: Case studies, human and social aspects
1. Developing an understanding for the core research problems surrounding evolving collective systems on the Web
2. Acquiring relevant background in fundamental computing techniques that are appropriate for understanding and designing such systems
3. Gaining an appreciation for the socioeconomic impact of these systems and the potential risks associated with them
D. Miorandi, V. Maltese, M. Rovatsos, A. Nijholt, J. Stewart (eds). Social Collective Intelligence. Combining the Powers of Humans and Machines to Build a Smarter Society, Computational Social Sciences Series, Springer-Verlag, 2014
M. Wooldridge. An Introduction to MultiAgent Systems, Second Edition, John Wiley & Sons, 2009. http://www.cs.ox.ac.uk/people/michael.wooldridge/pubs/imas/IMAS2e.html
S. Staab, S. Steffen, and R. Studer, eds. Handbook on Ontologies. Springer Science & Business Media, 2013. http://www.springer.com/gb/book/9783540709992
The course assumes some general mathematical and computational literacy, but will attempt to introduce all formal material and notation in such ways that background knowledge is kept to a minimum.
Michael Rovatsos is Director of the Centre for Intelligent Systems and their Applications and a Senior Lecturer in the School of Informatics. His research is in multiagent systems with a particular focus on algorithmic methods for resolving conflict among agents with divergent interests and viewpoints. Over the last few years, this focus has shifted toward human-oriented AI, both in terms of building intelligent systems to support human collaboration, and in developing human-inspired methods that enable artificial agents to learn to communicate like humans. He received his PhD in Informatics from the Technical University of Munich in 2004, and his first degree from Saarland University in 1999.Website