Invited Talks

Delivering the Smart Grid: A Grand Challenge for Autonomous Agents Research

Alex Rogers
University of Southampton
http://www.ecs.soton.ac.uk/people/acr

Restructuring electricity grids to meet the increased demand of electric vehicles and heat pumps, while making greater use of intermittent renewable energy sources, represents one of the greatest engineering challenges of our day. This modern electricity grid, in which both electricity and information flow in two directions between large numbers of widely distributed suppliers and generators - commonly termed the `smart grid' - represents a radical reengineering of infrastructure which has changed little over the last hundred years. However, the autonomous behaviour expected of the smart grid, its highly distributed nature, and the existence of multiple stakeholders each with their own incentives and interests, challenges existing engineering approaches. In this talk, I will describe why I believe that autonomous agents and multi-agent systems are essential for delivering the smart grid as it is envisioned. I will present some recent work that has been done in this area, and describe many challenges that still remain.

Lab and field evidence of a cognitive hierarchy in strategic thinking

Colin Camerer
California Institute of Technology
http://www.hss.caltech.edu/~camerer/camerer.html

When software agents interact with people, game theory provides a framework to help the agents make decisions. However, human behavior in games differs from that of the infinitely rational beings studied in classical game theory. Cognitive hierarchy (CH) models offer an algorithmic approach to modelling bounded rationality in strategic thinking, particularly for new strategic environments or as initial conditions for models of learning from experience. CH models have been applied to many experimental data sets, and to some field settings including Swedish lottery games and quality disclosure of movies through critics' reviews. There is also evidence from measuring visual attention, and fMRI of brain activity, which is consistent with steps of strategic thinking.

Social Contexts

Moshe Tennenholtz
Technion/Microsoft Research Israel
2012 ACM/SIGART Autonomous Agents research award winner
http://iew3.technion.ac.il/Home/Users/Moshet.phtml

This talk will advocate the explicit treatment of social contexts for the design of automated agents and multi-agent systems. In particular, I will illustrate how social contexts effect the design of optimization algorithms, how social contexts can be designed to lead to efficient and stable multi-agent systems, and how adopting assumptions about the nature of the social context can provide powerful solutions to classical challenges in game theory and reinforcement learning.

Social Norms for Self-Policing Multi-Agent Systems and Virtual Societies

Daniel Villatoro
Artificial Intelligence Research Institute, Spanish National Research Council
2011 Victor Lesser Distinguished Dissertation award winner
http://www.iiia.csic.es/~dvillatoro/

Social norms help people self-organizing in many situations where having an authority representative is not feasible. The responsibility to enforce such norms is not the task of a central authority but of each member of the society. In recent years, the use of social norms has been considered also as a mechanism to regulate virtual societies and specifically heterogeneous societies formed by humans and artificial agents. This talk outlines a game-theoretical categorization of norms, and considers how conventions emerge when dealing with different topological structures of interactions. It also explores incentive mechanisms (such as punishment) that allow the imposition of social norms, as well as mechanism by which agents comply with norms as an end in itself.