- Prof. dr. Peter McBurney, King’s College London, UK
Agent-Based Models: What Are They For?
Despite the growing popularity of agent-based modeling across the sciences, the social sciences, and in policy domains, domain experts and users only rarely stop to consider what these models are for. Indeed, the same is true for modeling in general; most model-users seem to take the purpose(s) of modeling for granted, and thus not needing any discussion. However, models and modeling activities typically have multiple stakeholders, who often have different and sometimes conflicting purposes in mind. In this talk, I will consider some of the different potential reasons that models are created and used, both in general and for agent-based models in particular. I will explore some of the implications of these different intended purposes, and I will argue for making explicit the stakeholders and goals of modeling activities prior to modeling.
- Prof. dr. Milind Tambe*, University of Southern California, USA
Game theory for security: A Fantastic Opportunity for Real-World Multiagent Systems Research
Security at major locations of economic or political importance or transportation or other infrastructure is a key concern around the world, particularly given the threat of terrorism. Limited security resources prevent full security coverage at all times; instead, these limited resources must be deployed intelligently taking into account differences in priorities of targets requiring security coverage, the responses of the adversaries to the security posture and potential uncertainty over the types of adversaries faced. Game theory is well-suited to adversarial reasoning for security resource allocation and scheduling problems. Casting the problem as a Bayesian Stackelberg game, we have developed new algorithms for efficiently solving such games to provide randomized patrolling or inspection strategies: we can thus avoid predictability and address scale-up in these security scheduling problems, addressing key weaknesses of human scheduling. Our algorithms are now deployed in multiple applications: ARMOR has been deployed at the Los Angeles International Airport (LAX) since 2007 to randomizes checkpoints and canine patrol; IRIS for randomized deployment of the Federal Air Marshals (FAMS) since 2009; PROTECT for scheduling US coast guard patrols, deployed in Boston and now headed to other ports in the US including New York; and GUARDS is under evaluation for national deployment by the Transportation Security Administration (TSA). Additional applications are underway for other police and security agencies. These applications are leading to real-world use-inspired research in computational game theory in scaling up to large-scale problems, handling significant adversarial uncertainty, dealing with bounded rationality of human adversaries, and other fundamental challenges. This talk will outline our algorithms, key research results and lessons learned from these applications.
* This is joint work with a large number of collaborators, including former and current students, postdocs, and other colleagues, listed at: http://teamcore.usc.edu/security
- Prof. dr. Marie-Pierre Gleizes, IRIT, Paul Sabatier University, Toulouse, France
Self-Adaptive Complex Systems
Nowadays and in the near future, complexity of computer applications is exponentially increasing. This complexity comes from the inherent properties of such an application: the great number of its involved components, the distribution of its control and skills, the nonlinearity of its process and its increasing openness. This is also caused by the unpredictable coupling with its environment due to high dynamicity. To fulfil these requirements, systems have to adapt themselves in order to be robust and efficient. For Robertson, adaptation provides means to a system to continue to reach its objective or to improve its behaviour.
This talk will deal with self-adaptation in software systems, particularly from a multi-agent viewpoint. It will focus on self-organizing mechanisms and emergence. Numerous applications already developed in this context will illustrate the different concepts. Then, the Adaptive Multi-Agent Systems theory which provides a guide to design self-organizing systems will be presented. This theory is based on the observation that the cooperation enables to guide the agent behaviour at the micro-level, helping the agents to self-organize and to obtain adaptation at the macro-level. The modification of the interactions between the agents of the system modifies also the global function and makes the system able to adapt to changes in its environment. The interactions between agents depend on the local view these agents have and on their ability to “cooperate” with each other. We propose also several criteria to evaluate the performance of such self-organizing software, from quantitative and qualitative points of view.
