Invited Speakers

We are delighted to announce three distinguished invited speakers at this workshop:

Agents that negotiate proficiently with people Sarit Kraus Adjunct Professor of Computer Science, University of Maryland Professor of Computer Science, Bar Ilan University, Israel

Abstract:

Negotiation is a process by which interested parties confer with the aim of reaching agreements. The dissemination of technologies such as the Internet has created opportunities for computer agents to negotiate with people, despite being distributed geographically and in time. The inclusion of people presents novel problems for the design of autonomous agent negotiation strategies. People do not adhere to the optimal, monolithic strategies that can be derived analytically, as is the case in settings comprising computer agents alone. Their negotiation behavior is affected by a multitude of social and psychological factors, such as social attributes that influence negotiation deals (e.g., social welfare, inequity aversion) and traits of individual negotiators (e.g., altruism, trustworthiness, helpfulness).

In this talk I will present the following two agents that negotiate well with people by modeling several social factors: The PURB agent that can adapt successfully to people from different cultures in complete information settings, and the SIGAL agent that learns to negotiate successfully with people in games where people can choose to reveal private information. These agents were evaluated in extensive experiments including people from three countries. I will also demonstrate how agents' opponent modeling of people can be improved by using models from the social sciences and how Peer-Designed-Agents - agents that were designed by non-experts to represent themselves during negotiation - can help in evaluating negotiating agents.

Biosketch:

Sarit Kraus (Ph.D. Computer Science, Hebrew University, 1989) is a Professor of Computer Science at Bar-Ilan University and Adjunct Professor at the Institute for Advanced Computer Studies, University of Maryland. She worked extensively in the following areas: the development of intelligent systems, negotiation and cooperation in mixed open environments (including people), personalization, learning and clustering, optimization of complex systems and security of physical systems. In 1995 Kraus was awarded the IJCAI Computers and Thought Award (the premier award for a young AI scientist). In 2001 she was awarded the IBM Faculty Partnership Award and in 2002 she was elected as AAAI fellow. In 2007 she was awarded the ACM SIGART Agents Research award and her paper with Prof. Barbara Grosz was a winner of the IFAAMAS influential paper award (joint winner). In 2008 she was elected as ECCAI fellow and in 2010 she was awarded the EMET prize. She has published over 270 papers in leading journals and major conferences and is an author of the book Strategic Negotiation in Multiagent Environments(2001) and a co-author of a book on Heterogeneous Active Agents (2000); both published in MIT Press.

Incomplete knowledge and communication issues in voting Jérôme Lang Senior Resercher at CNRS, Paris, France

Abstract:

Computational social choice is a rapidly emerging research topic, located at the crossing point between social choice and computer science (and especially AI). One of the key problems in computational social choice is the determination of the winning alternative(s) when the knowledge about the voters' preferences is incomplete. This incompleteness may have several possible causes: voters who forget to send their vote, as typical in Doodle polls; new candidates appearing in the course of the process, on which the voters haven't expressed any opinion yet; voters refusing to compare two alternatives because their preference depends on an exogenous event; etc. In these situations, one may try to identify the alternatives that can still win when the voters' preferences are eventually fully known, and one may also try to build interactive protocols for asking the agents enough of the missing information so as to be able to compute the winning alternative(s) while trying to minimize the amount of communication. This talk will give a survey of this hot topic, and relate it to closely related issues, such as the computational resistance to strategic behaviour.

Biosketch:

Jérôme Lang is a senior researcher ("directeur de recherche") at Centre National de la Recherche Scientifique. Since 2008 he is affiliated with the Laboratoire d'Analyse et de Modélisation de Systèmes d'Aide à la Décision (LAMSADE), Université Paris-Dauphine.

From 1991 to 2008 he was a CNRS researcher at Institut de Recherche en Informatique de Toulouse. His research interests span a large part of Artificial Intelligence, especially Knowledge Representation and Multi-Agent Systems. His recent research activities focus on preference representation and computational social choice.

Propagation Dynamics of Beliefs in Large Heterogeneous Networks Katia Sycara Professor, Carnegie Mellon University, USA. Director of the Intelligent Software Agents Lab

Abstract:

Large scale networked systems that include heterogeneous entities, e.g. humans and computational entities are becoming increasingly prevalent. Prominent applications include the Internet, large scale disaster relief and network centric warfare. In such systems, large heterogeneous coordinating entities exchange uncertain information to obtain and increase situation awareness. Uncertain and possibly conflicting sensor data is shared across a peer-to-peer network. Not every team member will have direct access to sensors and team members will be influenced mostly by their neighbors in the network with whom they communicate directly. In this talk I will present our work on the dynamics and emergent behaviors of belief propagation in such large networks. Unlike past work, the nodes in the networks we study are autonomous and actively fuse information they receive. Nodes can change their beliefs as they receive additional information over time.

A key property of the system is that it exhibits qualitatively different dynamics and system performance over different ranges of system parameters. In one particular range, the system exhibits behavior known as scale-invariant dynamics which we empirically find to correspond to dramatically improved system performance. I will present results on the emergent belief propagation dynamics in those systems, mathematical characterization of the systems' behavior and distributed algorithms for adapting the network behaviors to steer the whole system to areas of optimized performance.

Biosketch:

Katia Sycara is a Professor in the School of Computer Science at Carnegie Mellon University and Director of the Laboratory for Agents and Semantic Technologies. She holds the Sixth Century Chair at the University of Aberdeen (UK). She holds a PhD in Computer Science from Georgia Institute of Technology and a Doctorate Honoris Causa from the University of the Aegean. She is a Fellow of the Institute of Electronic and Electrical Engineers (IEEE), a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) and the recipient of the 2002 ACM/SIGART Agents Research Award.

She has authored more than 350 technical papers dealing with Multi-Agent and Multi-Robot Systems, Semantic Web Services, Human-Robot Interaction, Negotiation, Case-Based Reasoning, Multi-Agent Learning, Large Networked Systems and Social Networks. She contributed to the development of OWL-S, a language for Semantic Web services. From 2001-2003 she served as Invited Expert of the W3C (the World Wide Web Consortium) Working Group on Web Services Architecture. She served as a member of the Scientific Advisory Board of France Telecom (2006-2010). She co-founded "Autonomous Agents and Multi Agent Systems", and served as its Editor-in-Chief. She is on the editorial board of additional 7 journals. She is a Founding member of the International Foundation of Autonomous Agents and Multi-Agent Systems (IFAAMAS) and of the US-EU Web Science Association.