42 citations · 134 across the 9 of their papers we have counts for
9 papers
Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the MACHIAVELLI Benchmark
Alexander Pan, Jun Shern Chan, Andy Zou +7
Artificial agents have traditionally been trained to maximize reward, which may incentivize power-seeking and deception, analogous to how next-token prediction in language models (…
imitation: Clean Imitation Learning Implementations
Adam Gleave, Mohammad Taufeeque, Juan Rocamonde +7
imitation provides open-source implementations of imitation and reward learning algorithms in PyTorch. We include three inverse reinforcement learning (IRL) algorithms, three imita…
For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria
Scott Emmons, Caspar Oesterheld, Andrew Critch +2
Although it has been known since the 1970s that a globally optimal strategy profile in a common-payoff game is a Nash equilibrium, global optimality is a strict requirement that li…
An Empirical Investigation of Representation Learning for Imitation
Xin Chen, Sam Toyer, Cody Wild +9
Imitation learning often needs a large demonstration set in order to handle the full range of situations that an agent might find itself in during deployment. However, collecting e…
RvS: What is Essential for Offline RL via Supervised Learning?
Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov +1
Recent work has shown that supervised learning alone, without temporal difference (TD) learning, can be remarkably effective for offline RL. When does this hold true, and which alg…
Sparse Graphical Memory for Robust Planning
Scott Emmons, Ajay Jain, Michael Laskin +3
To operate effectively in the real world, agents should be able to act from high-dimensional raw sensory input such as images and achieve diverse goals across long time-horizons. C…
Concurrency and reachability in tree-like temporal networks
Eun Lee, Scott Emmons, Ryan Gibson +2
Network properties govern the rate and extent of various spreading processes, from simple contagions to complex cascades. Recently, the analysis of spreading processes has been ext…
A Map Equation with Metadata: Varying the Role of Attributes in Community Detection
Scott Emmons, Peter J. Mucha
Much of the community detection literature studies structural communities, communities defined solely by the connectivity patterns of the network. Often, networks contain additiona…
Post-processing partitions to identify domains of modularity optimization
William H. Weir, Scott Emmons, Ryan Gibson +2
We introduce the Convex Hull of Admissible Modularity Partitions (CHAMP) algorithm to prune and prioritize different network community structures identified across multiple runs of…