NYU Prof. Ernest Davis on "Simulation in Cognitive Models: Scope and Limits"

Artificial Intelligence agents that want to understand the world around them, need to be able to reason on how physical objects interact with each other, that is to perform "physical reasoning". On Feb 23rd at 6:30PM EST, we are excited to have New York University Prof. Ernest Davis present his talk "Simulation in Cognitive Models: Scope and Limits", to shed some light on how physical reasoning processes may work.

We are thankful to Ebay for graciously hosting us at their office (625 Ave of Americas (6th ave bw. 18th and 19th St.) 3rd floor). Light refreshments will be served. Also our thanks go to our partner Venrock: if you are an entrepreneur and have ideas on how to use Cognitive Artificial Intelligence, please make sure to attend and get in touch.

Slides will be available after the talk. Please RSVP, providing your full names and email for access to the building.

We look forward to seeing you there!

Stefano & Chris

Title: Simulation in Cognitive Models: Scope and Limits

Abstract: It has been proposed that human physical reasoning consists largely of running "physics engines in the head" in which the future trajectory of the physical system under consideration is computed precisely using accurate scientific theories. In such models, uncertainty and incomplete knowledge is dealt with by sampling probabilistically over the space of possible trajectories ("Monte Carlo simulation"). We argue that such simulation-based models are too weak, in that there are many important aspects of human physical reasoning that cannot be carried out this way, or can only be carried out very inefficiently; and too strong, in that humans make large systematic errors that the models cannot account for. We conclude that simulation-based reasoning makes up at most a small part of a larger system that encompasses a wide range of additional cognitive processes. (Joint work with Gary Marcus)

Bio: Ernest Davis is Professor of Computer Science at New York University, His research area is automated commonsense reasoning, particularly commonsense spatial and physical reasoning. He is the author of Representing and Acquiring Geographic Knowledge (1986), Representations of Commonsense Knowledge (1990) and Linear Algebra and Probability for Computer Science Applications (2012); and coeditor of Mathematics, Substance and Surmise; Views on the Meaning and Ontology of Mathematics (2015).