The aim of this course is to introduce the mathematical theory and algorithmic results about graph-games, to convey how graph-games form the foundation of formal-methods, and how they are used in AI.

Sasha Rubin, University of Naples “Federico II”.

The course is given in a block format between November 20. and December 1, 2017.

Student presentations are scheduled for the subsequent week (4.12.–8.12).

20.11.2017–01.12.2017 | 10:00–12:00 | Seminar Room Neumann |

21.11.2017 | 14:00–16:00 | Seminar Room Neumann |

23.11.2017 | 14:00–16:00 | Seminar Room Zemanek |

28.11.2017 | 14:00–16:00 | Seminar Room Neumann |

30.11.2017 | 14:00–16:00 | Seminar Room Zemanek |

Games on graphs are a useful mathematical model of many phenomena in computer science that involve interaction between players/agents/components. Solving a game means deciding if a given player has a winning strategy. There are a number of classes of games whose complexity are in the intersection of NP and co-NP, but are not known to be in P, i.e., parity games, mean-payoff games, discounted payoff games, simple stochastic games. This year, there was a breakthrough in the analysis of parity games, a deceptively simply class of games with tight connections to deep results in logic and automata theory. A team from New Zealand and Singapore [Calude et. al. 2017] gave a quasi-polynomial time algorithm for solving parity games — previous algorithms were mildly subexponential.

I will chart a course through the theory of games on graphs, covering determinacy, memory required for winning, and the complexity of solving games. I will start with foundational work and end with very recent results.

I will draw material from the following core papers:

– Ehrenfeucht and Mycielski (1979). Positional strategies for mean payoff games.

– McNaughton (1993). Infinite games played on finite graphs.

– Zwick and Paterson (1995). The complexity of mean payoff games.

– Dziembowski, Jurdzinski, and Walukiewicz (1997). How much memory is needed to win infinite games?

– Zielonka (1998). Infinite games on finitely coloured graphs with applications to automata on infinite trees.

– Voge and Jurdzinski (2000). A discrete strategy improvement algorithm for solving parity games.

– Chatterjee, Henzinger, and Jurdzinski (2005). Mean-payoff parity games.

– Schewe (2007). Solving Parity Games in Big Steps.

– Jurdzinski, Paterson, and Zwick (2008). A deterministic subexponential algorithm for solving parity games.

– Friedmann (2009). An exponential lower bound for the parity game strategy improvement algorithm as we know it.

– Benerecetti, Dell’Erba and Mogavero (2016). Solving parity games via priority promotion.

– Aminof and Rubin (2016). First Cycle Games.

– Calude, Jain, Khoussainov, Li, and Stephan (2017). Deciding parity games in quasipolynomial time.

– Jurdzinski and Lazic (2017). Succinct progress measures for solving parity games.

**For credit, participants can give a talk on a classic or current paper.**

There are a variety of topics to choose from: the tight connection between graph-games and logic and automata-theory, the use of graph-games in formal-methods (modeling, verification, synthesis, testing, composition, simulation), the use of graph-games in AI (automated planning, verification in robotics, general-game playing), or extensions of the basic model (multiplayer games, partial-information games, stochastic games, pushdown games, timed games).

- Apt, Krzysztof R. and Erich Gradel (Eds.). 2011. Lectures in Game Theory for Computer Scientists. Cambridge University Press: Cambridge.
- Grädel, Erich, Wolfgang Thomas and Thomas Wilke (Eds.). 2002. Automata, Logics, and Infinite Games: A Guide to Current Research. Springer-Verlag New York: New York.

- Visit our Facebook page Vienna Center for Logic and Algorithms at TU Wien – VCLA
- Share on Twitter with @vclaTUwien
- Watch on Youtube Vienna Center for Logic and Algorithms
- Find your Waldo on Flickr (CC BY 4.0 & CCO) as Vienna Center for Logic and Algorithms at TU Wien

Every coin has two sides, and social media is no exception. It can run the risk of being a source of misinformation, but it can also be an effective way to redirect that information. Among other, scientist use social media to their advantage to gain more media attention, potential collaborators, job opportunities and funding opportunities (AAAS 2017, FWF 2017).

The crux of the mater of open science initiatives, taken over also by the funding bodies of VCLA seems to be: In order for members of the civil society to participate meaningfully in dialogue on science and socioeconomic development they need to be informed. The major sources of knowledge available to them are not the peer-reviewed journals and conference proceedings that are the kit and caboodle of academia (SIRC 2006, ERC 2017).

- American Association for Advancement of Science (AAAS). 2017.
*Communicating Science Online*. - European Research Council (ERC). 2017.
*Communication your research*. - FWF. 2017.
*Open Access Policy für vom FWF geförderte Projekte*. - Mojarad, Sarah. 2017.
*Social media: More scientists needed*. In Science 357(6358), 1362-1363. - NUCLEUS. 2017.
*Resource*s. - RRI Tools. 2017.
*The EU guide to Science Communication*. - Social Issues Research Center (SIRC). 2006.
*Guidelines for scientists on communicating with the media*.

The future of robotics raises important questions for humanity. Will robots be able to act as agents in their own right and make moral and ethical decisions? Impressive advances in artificial intelligence mean robots may become capable of replacing human beings in every task imaginable. What are the ethical implications of such a development? How do we prepare for such a future? Questions on the ethics and morality of robotics will be debated by panelists specializing in ethics, law, computer science, data security and privacy, in the Oxford Union Debating Chamber, which has seen important international figures such as former US Secretary of State John Kerry, physicist Prof. Stephen Hawking, evolutionary biologist Prof. Richard Dawkins.

The panel will be chaired by Judy Wajcman (Anthony Giddens Professor of Sociology at the London School of Economics and Political Science) and will feature the following speakers:

Luciano Floridi (Professor of Philosophy and Ethics of Information, University of Oxford)

Ben Kuipers (Professor of Computer Science and Engineering—specializing in robotics, University of Michigan)

Francesca Rossi (Professor of Computer Science—specializing in artificial intelligence, University of Padova)

Matthias Scheutz (Professor of Computer Science—with a background in logic and cognitive science, Tufts University)

Sandra Wachter (Lawyer and Postdoctoral Researcher, University of Oxford and Alan Turing Institute), and

Jeannette Wing (Avanessians Director of the Data Sciences Institute at Columbia University, former VP of Microsoft Research with expertise in security and privacy.