40 citations · 83 across the 10 of their papers we have counts for
11 papers
Non-Stationary Policy Learning for Multi-Timescale Multi-Agent Reinforcement Learning
Patrick Emami, Xiangyu Zhang, David Biagioni +1
In multi-timescale multi-agent reinforcement learning (MARL), agents interact across different timescales. In general, policies for time-dependent behaviors, such as those induced…
Plug & Play Directed Evolution of Proteins with Gradient-based Discrete MCMC
Patrick Emami, Aidan Perreault, Jeffrey Law +2
A long-standing goal of machine-learning-based protein engineering is to accelerate the discovery of novel mutations that improve the function of a known protein. We introduce a sa…
From Model-Based to Model-Free: Learning Building Control for Demand Response
David Biagioni, Xiangyu Zhang, Christiane Adcock +3
Grid-interactive building control is a challenging and important problem for reducing carbon emissions, increasing energy efficiency, and supporting the electric power grid. Curren…
PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems
David Biagioni, Xiangyu Zhang, Dylan Wald +4
We present the PowerGridworld software package to provide users with a lightweight, modular, and customizable framework for creating power-systems-focused, multi-agent Gym environm…
A Comparison of Model-Free and Model Predictive Control for Price Responsive Water Heaters
David J. Biagioni, Xiangyu Zhang, Peter Graf +2
We present a careful comparison of two model-free control algorithms, Evolution Strategies (ES) and Proximal Policy Optimization (PPO), with receding horizon model predictive contr…
A Modular and Transferable Reinforcement Learning Framework for the Fleet Rebalancing Problem
Erotokritos Skordilis, Yi Hou, Charles Tripp +3
Mobility on demand (MoD) systems show great promise in realizing flexible and efficient urban transportation. However, significant technical challenges arise from operational decis…
On the Computational Viability of Quantum Optimization for PMU Placement
Eric B. Jones, Eliot Kapit, Chin-Yao Chang +4
Using optimal phasor measurement unit placement as a prototypical problem, we assess the computational viability of the current generation D-Wave Systems 2000Q quantum annealer for…
Learning-Accelerated ADMM for Distributed Optimal Power Flow
David Biagioni, Peter Graf, Xiangyu Zhang +3
We propose a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) whe…
Synthesis of a mixed-valent tin nitride and considerations of its possible crystal structures
Christopher M. Caskey, Aaron Holder, Sarah Shulda +20
Recent advances in theoretical structure prediction methods and high-throughput computational techniques are revolutionizing experimental discovery of the thermodynamically stable…
Randomized Interpolative Decomposition of Separated Representations
David J. Biagioni, Daniel Beylkin, Gregory Beylkin
We introduce tensor Interpolative Decomposition (tensor ID) for the reduction of the separation rank of Canonical Tensor Decompositions (CTDs). Tensor ID selects, for a user-define…
Keeping greed good: sparse regression under design uncertainty with application to biomass characterization
David J. Biagioni, Ryan Elmore, Wesley Jones
In this paper, we consider the classic measurement error regression scenario in which our independent, or design, variables are observed with several sources of additive noise. We…