Invited speakers
Francesco Belardinelli (Imperial College, London)
Information and Memory in the Verification of Multi-agent Systems
Information and memory are two key dimensions in the analysis of multi-agent systems (MAS). Having perfect or imperfect information, resp. memory, about the state of the system has a dramatic impact on the strategic abilities of agents, including the complexity of MAS verification. In the worst-case, when agents have imperfect information and perfect recall, the model checking problem for the Alternating-time Temporal Logic (ATL) becomes undecidable. Unfortunately, this setting is of interest for several applications, including communications and security protocols.
In this talk I will review some recent advances that tackle this undecidable problem by approximating either information or memory, by using three-valued abstractions. Intuitively, the model checking algorithms for three-valued ATL return an undefined truth value whenever there is not enough information or memory to decide the specification at hand in the standard two-valued semantics. Refinement procedures are then put in place to add either information or memory, with the goal of providing a defined answer.
This talk is based on joint work with Vadim Malvone (Telecom Paris) and Alessio Lomuscio (Imperial College London) that has been published in KR&R18, AAAI19, and KR&R20.
Moshe Vardi (Rice University, Houston)
Lessons from COVID-19: Efficiency vs Resilience
In both computer science and economics, efficiency is a cherished property. In computer science, the field of algorithms is almost solely focused on their efficiency. In economics, the main advantage of the free market is that it promises "economic efficiency". A major lesson from COVID-19 is that both fields have over-emphasized efficiency and under-emphasized resilience. We argue that resilience is a more important property than efficiency and discuss how the two fields can broaden their focus to make resilience a primary consideration. I will conclude with a technical example, showing how we can shift the focus in strategic reasoning from efficiency to resilience.