Select a calendar:
Filter April Events by Event Type:
SUNMONTUEWEDTHUFRISAT
Events for April 04, 2023
-
ECE-Controls Faculty Candidate Seminar - Dr Steve Alpern
Tue, Apr 04, 2023 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr Steve Alpern, Professor, University of Warwick
Talk Title: The Faulty GPS Problem: Optimal Search for Home Node on a Network, with Unreliable Directions
Abstract: Searcher wants to find the Home node on a given Network, but his directions are unreliable. At every branch node of a network Q, a Satnav (GPS) points to the arc leading to the destination, or home node, H - but only with a high known probability p. The pointer is fixed in time, so does not change when a node is revisited. Always trusting the Satnav's suggestion may lead to an infinite cycle. If one wishes to reach H in least expected time, with what probability q=q(Q,p) should one trust the pointer (if not, one chooses randomly among the other arcs)? We call this the Faulty Satnav (GPS) Problem. We also consider versions where the trust probability q can depend on the degree of the current node and a `treasure hunt' where two searchers try to reach H first. The agent searching for H need not be a car, that is just a familiar example -- it could equally be a UAV receiving unreliable GPS information.
This problem has its origin not in driver frustration but in the work of Fonio et al (2017) on ant navigation, where the pointers correspond to pheromone markers pointing to the nest.
Biography: Steve did his AB in Mathematics at Princeton, supervised by Oskar Morgenstern, and his PhD in Ergodic Theory at Courant Institute -“ NYU, under Peter Lax. He moved from ergodic theory to game theory and search theory mid career. After many years at the London School of Economics, he moved to the University of Warwick, where he is Professor of Operational Research.
Host: Dr Petros Ioannou, ioannou@usc.edu | Dr George Papavissilopoulos, yorgos@netmode.ece.ntua.gr
Webcast: https://usc.zoom.us/j/96085498483?pwd=aXJ4U244VHhQOCtIUURDM29mb216UT09More Information: ECE-Controls_Seminar_Announcement.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
WebCast Link: https://usc.zoom.us/j/96085498483?pwd=aXJ4U244VHhQOCtIUURDM29mb216UT09
Audiences: Everyone Is Invited
Contact: John Diaz
-
CS Colloquium: Rakshit Trivedi (MIT) - Foundations for Learning in Multi-agent Ecosystems: Modeling, Imitation, and Equilibria
Tue, Apr 04, 2023 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Rakshit Trivedi, MIT
Talk Title: Foundations for Learning in Multi-agent Ecosystems: Modeling, Imitation, and Equilibria
Series: CS Colloquium
Abstract: The growing presence of AI in critical domains such as information communication, service, financial markets and agriculture requires designing AI systems capable of seamlessly interacting with other AI, with humans and as part of complex systems in a manner that is beneficial to humans. For an AI to be effective in such settings, a key open challenge is for it to have the ability to effectively collaborate across a broad group of interdependent agents (AI or human) in a variety of one or few-shot interactions. A crucial step towards addressing this is to enable rapid development and safe evaluation of AI agents and frameworks that can incorporate the richness and diversity observed in human behaviors and account for various social and economic factors that drives interactions in the multi-agent ecosystems. In this talk, I will set forth the research agenda of real-world in silico design for such AI systems and discuss methodological advancements in this direction. First, I will focus on automated design of central mechanisms tasked to shape the behavior of self-interested agents and drive them towards improving social welfare. I will introduce a novel multi-agent reinforcement learning technique to solve the resulting bi-level optimization problem and present its effectiveness in a simulated market economy. Next, I will discuss the setting where the self-interested agents interact with each other in a strategic manner to form networks and present our approach on discovering the underlying mechanisms that drives these interactions. This approach considers a game-theoretic formalism, and leverages recent advances in inverse reinforcement learning, thereby serving as a preliminary step towards learning models of optimizing mechanisms directly from observed data. Finally, I will focus on the use of AI agents as surrogate for human actors that can provide simulations of real-world complexity and discuss challenges and opportunities on designing AI that is capable of handling the diversity, richness, and noise that is inherent to human behaviors. I will conclude my talk with an outline of my forward-looking vision on this agenda.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Rakshit Trivedi is a Postdoctoral Associate in the Computational Science and Artificial Intelligence Laboratory (CSAIL) at MIT and a Researcher in EconCS at Harvard School of Engineering and Applied Sciences (SEAS). His research focuses on the development of AI that is capable of learning from human experiences, quickly adapt to evolving human needs and achieve alignment with human values. He is further interested in studying the effectiveness of such an AI in the presence of various socio-economic mechanisms. Towards this goal, he is currently leading a set of efforts on developing and evaluating design strategies for building helpful and prosocial artificial agents in mixed-motive settings, in collaboration with Deepmind and Cooperative AI Foundation. Previously, Rakshit completed his Ph.D. at Georgia Institute of Technology, where he focused on learning in networked and multi-agent systems to improve predictive and generative capabilities of downstream applications, by accounting for the structure and dynamics of interactions in such systems.
Host: Bistra Dilkina
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
-
Photonics Seminar - Antonio Rigol, Tuesday, April 4th at 3pm in EEB 248
Tue, Apr 04, 2023 @ 03:00 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Marcos Antonio Rigol, Physics, Penn State
Talk Title: Typical eigenstate entanglement entropy as a diagnostic of quantum chaos and integrability
Series: Photonics Seminar Series
Abstract: The typical entanglement entropy of subsystems of random pure states is known to be (nearly) maximal, while the typical entanglement entropy of random Gaussian pure states has been recently shown to exhibit a qualitatively different behavior, with a coefficient of the volume law that depends on the fraction of the system that is traced out. We review evidence that the typical entanglement entropy of eigenstates of quantum-chaotic Hamiltonians mirrors the behavior in random pure states, while that of integrable Hamiltonians mirrors the behavior in random Gaussian pure states. Based on these results, we conjecture that the typical entanglement entropy of Hamiltonian eigenstates can be used as a diagnostic of quantum chaos and integrability. We discuss subtleties that emerge as a consequence of conservation laws, such as particle number conservation, as well as of lattice translational invariance.
Biography: Dr. Rigol is a Professor of Physics at Penn State. Before joining Penn State, he was an Associate Professor of Physics at Georgetown University. Dr. Rigol completed his undergraduate (Summa Cum Laude) and M.Sc. studies at the Institute of Nuclear Sciences and Technology in Havana. He received his Ph.D.
in Physics (Summa Cum Laude) from the University of Stuttgart, and did postdocs at the University of California Davis, the University of Southern California, and the University of California Santa Cruz.
Dr. Rigol research interest is in many-body quantum systems in and out of equilibrium, with a focus on the effect of strong correlations. His research is at the interface between condensed matter physics, ultracold atoms, and statistical mechanics. He is a Fellow of the American Physical Society and of the American Association for the Advancement of Science.
Host: Mercedeh Khajavikhan, Michelle Povinelli, Constantine Sideris; Hossein Hashemi; Wade Hsu; Mengjie Yu; Wei Wu; Tony Levi; Alan E. Willner; Andrea Martin Armani
More Information: Marcos Antonio Rigol Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
-
Epstein Institute - ISE 651 Seminar
Tue, Apr 04, 2023 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Yuri Faenza, Associate Professor, Dept. of Industrial Engineering and Operations Research, Columbia University
Talk Title: Stable Matchings in Choice Function Models: Theory and Applications to School Choice
Host: Dr. Giacomo Nannicini
More Information: April 4, 2023.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - GER 206
Audiences: Everyone Is Invited
Contact: Grace Owh
