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3	3	== Speakers ===
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6		-((( [[image:michael1.jpg]]
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7	7	=== [[Michael Mäs>>http://www.maes-sociology.eu/]] ===
8	8
9	9	**What can social-influence models teach us about the design of personalized recommender systems?**
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16	16	Third, I will discuss implications of social-influence models for the development of personalized recommender systems. I will sketch different approaches to developing systems that generate personalized outcomes without fostering opinion polarization. I will show that such systems cannot be developed without an accurate model of social influence.
17	17	On a more general level, I will conclude that the development of technologies on the Internet that have the potential to affect societal dynamics should be guided by theoretical and empirical research. In models of complex systems, even small and seemingly innocent differences in the assumptions about the underlying micro-mechanisms can have critical effects on macro-outcomes. As information technology affects micro-mechanisms, it crucial to understand possible consequences before it is too late to intervene.
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26		-==== [[Franco Zambonelli>>http://www.agentgroup.unimore.it/Zambonelli/]] ====
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	23	+=== [[Franco Zambonelli>>http://www.agentgroup.unimore.it/Zambonelli/]] ===
	24	+**Coordination in Urban-scale Heterogeneous Multiagent Systems**
	25	+>Most of the emerging scenarios in the area of software-intensive systems and smart cities involve a very large number of interacting autonomous components (i.e., agents). In my talk, I argue that the peculiar features of such emerging multiagent systems (up to millions of interacting components, geographically-distributed over vast areas, mixing humans and artificial components, and lacking any form of central control) call for radically novel approaches to coordinate their overall activities and functionalities. In particular, during the talk, I will overview some representative scenarios of emerging large-scale multiagent systems in the area of urban computing, discuss the key challenges to be faced by research in coordination models and technologies, and eventually sketch some promising research directions.
	26	+)))
27	27
28		- <p>**Coordination in Urban-scale Heterogeneous Multiagent Systems**</p>
29		-<p/>
30		- <p>Most of the emerging scenarios in the area of software-intensive systems and smart cities involve a very large number of interacting autonomous components (i.e., agents). In my talk, I argue that the peculiar features of such emerging multiagent systems (up to millions of interacting components, geographically-distributed over vast areas, mixing humans and artificial components, and lacking any form of central control) call for radically novel approaches to coordinate their overall activities and functionalities. In particular, during the talk, I will overview some representative scenarios of emerging large-scale multiagent systems in the area of urban computing, discuss the key challenges to be faced by research in coordination models and technologies, and eventually sketch some promising research directions.</p>
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38		- [[image:marc.jpg]]
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42		-==== [[Marc Cavazza>>https://ive.scm.tees.ac.uk/?pID=5&aID=4]] ====
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44		- <p>**Brain-Computer Interfacing to Agents**</p>
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46		- <p>Brain-Computer Interfaces (BCI) have attracted significant interest as an interaction technique, beyond their original potential for assistive technologies. While BCI are often seen as a low bandwidth input mechanism to control devices, they can also open a window on some high-level cognitive functions such as executive decision-making, risk taking and affective regulation. This is a consequence of the ability of BCI techniques to acquire signals from various areas of the brain, such as the prefrontal cortex.
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	29	+(((
	30	+[[image:marc.jpg]]
	31	+=== [[Marc Cavazza>>https://ive.scm.tees.ac.uk/?pID=5&aID=4]] ===
	32	+**Brain-Computer Interfacing to Agents**
	33	+Brain-Computer Interfaces (BCI) have attracted significant interest as an interaction technique, beyond their original potential for assistive technologies. While BCI are often seen as a low bandwidth input mechanism to control devices, they can also open a window on some high-level cognitive functions such as executive decision-making, risk taking and affective regulation. This is a consequence of the ability of BCI techniques to acquire signals from various areas of the brain, such as the prefrontal cortex.
47	47	In this talk, I will present recent and ongoing research exploring Brain-Computer Interfacing to agents, considering both virtual agents and rational agents. We have used several BCI techniques (EEG, fNIRS) to capture the activity of the prefrontal cortex in real-time, with a specific emphasis on measuring prefrontal cortex asymmetry. I will discuss how this type of BCI can be used in various agents systems, from communicating with Embodied Conversational Agents to influencing the behaviour of a heuristic search algorithm.
48		-Finally, I will discuss the new perspectives that BCI research could bring to some popular topics in Agents research.</p>
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	35	+Finally, I will discuss the new perspectives that BCI research could bring to some popular topics in Agents research.
	36	+)))