Kurenkov
Reinforcement learning (RL) is one of the basic subfields within Artificial Intelligence. In an RL framework, an agent interacts with an environment to learn what actions it needs to take in any given environment state to maximize its long-term reward. Despite the major accomplishments of the last two years (such as DeepMind's AlphaGo and AlphaZero, as well as OpenAI's Dota bots), RL is fundamentally flawed and more complex accomplishments may not be possible under pure RL. Different approaches within AI can address those limitations.

Jiang
Within the next 10 to 20 years, many jobs will be replaced by robots, including not only labor intensive work such as drivers and factory workers, but jobs that were thought to be safe from takeover, like law and technical writing. However, our education systems have barely changed in this same 10 to 20-year time period. We may very well be churning out students that have few job prospects upon their graduation. A deep understanding of robotics and AI is necessary to design education systems that will produce people who will collaborate with robots instead of competing with robots in the near future.

Stork
The problem of fake, forged and misattributed paintings in museum and private collections and in the broader commercial art market is large and unrecognized by much of the art community and the art-loving public. The economic cost of such fake art may be as high as a trillion dollars worldwide, and the cost to our cultural understanding and patrimony is beyond estimation. This talk will begin with a brief overview of the classes of fake art (forgeries, fakes, copies, misattributions, ...), some of the motivations of forgers and their accomplices such as dealers and restorers, and the social, business, academic, and other forces that make it difficult to identify fake art and remove it from circulation. It will describe the intriguing world and motivations of master forgers such as Han van Meegeren, Wolfgang Beltracci, Mark Landis, and others, and describe key discoveries, such as the recent revelation that 82 out of the 140 works in the Terrus Museum are fake. and examples, such as the quirky $10m lawsuit against artist Peter Doig for not proving that he did not paint a work attributed to him. The talk will also describe briefly some of the methods for authenticating art and detecting fakes, such as the analysis of medium (oil, watercolor, ...) and support (paper, canvas, ...), the role of provenance (documentary history of ownership of works), iconography, computer image analysis, and the role of connoisseurship.

Brown
What does it mean for a work of art to be considered a forgery, and what does the idea of authenticity in art imply? What does it mean for an artwork to be real, and why do we value the real so highly? And what is the role of museums in determining what's authentic and what isn't? In 1929, collector Eila Haggin McKee bought what she thought was a painting by Gauguin. The painting hung in Stockton's Haggin Museum for over seventy-five years.before it was labeled a forgery. In this talk, drawn from research I have conducted for the Haggin, I will examine the history of ownership of this painting before 1929, and the tumultuous art world of 1890s Paris that may have seen its creation. Finally, through this painting's particular story, I will investigate the ways that scholars determine authenticity, and the relationship between museums, as guardians of the real, and their public.