13 citations · 34 across the 9 of their papers we have counts for
11 papers
DE-HNN: An effective neural model for Circuit Netlist representation
Zhishang Luo, Truong Son Hy, Puoya Tabaghi +7
The run-time for optimization tools used in chip design has grown with the complexity of designs to the point where it can take several days to go through one design cycle which ha…
Human Control: Definitions and Algorithms
Ryan Carey, Tom Everitt
How can humans stay in control of advanced artificial intelligence systems? One proposal is corrigibility, which requires the agent to follow the instructions of a human overseer,…
Reasoning about Causality in Games
Lewis Hammond, James Fox, Tom Everitt +3
Causal reasoning and game-theoretic reasoning are fundamental topics in artificial intelligence, among many other disciplines: this paper is concerned with their intersection. Desp…
Path-Specific Objectives for Safer Agent Incentives
Sebastian Farquhar, Ryan Carey, Tom Everitt
We present a general framework for training safe agents whose naive incentives are unsafe. As an example, manipulative or deceptive behaviour can improve rewards but should be avoi…
Too Big to Fail? Active Few-Shot Learning Guided Logic Synthesis
Animesh Basak Chowdhury, Benjamin Tan, Ryan Carey +3
Generating sub-optimal synthesis transformation sequences ("synthesis recipe") is an important problem in logic synthesis. Manually crafted synthesis recipes have poor quality. Sta…
A Complete Criterion for Value of Information in Soluble Influence Diagrams
Chris van Merwijk, Ryan Carey, Tom Everitt
Influence diagrams have recently been used to analyse the safety and fairness properties of AI systems. A key building block for this analysis is a graphical criterion for value of…
Why Fair Labels Can Yield Unfair Predictions: Graphical Conditions for Introduced Unfairness
Carolyn Ashurst, Ryan Carey, Silvia Chiappa +1
In addition to reproducing discriminatory relationships in the training data, machine learning systems can also introduce or amplify discriminatory effects. We refer to this as int…
Agent Incentives: A Causal Perspective
Tom Everitt, Ryan Carey, Eric Langlois +2
We present a framework for analysing agent incentives using causal influence diagrams. We establish that a well-known criterion for value of information is complete. We propose a n…
Incentives for Responsiveness, Instrumental Control and Impact
Ryan Carey, Eric Langlois, Chris van Merwijk +2
We introduce three concepts that describe an agent's incentives: response incentives indicate which variables in the environment, such as sensitive demographic information, affect…
(When) Is Truth-telling Favored in AI Debate?
Vojtěch Kovařík, Ryan Carey
For some problems, humans may not be able to accurately judge the goodness of AI-proposed solutions. Irving et al. (2018) propose that in such cases, we may use a debate between tw…
Incorrigibility in the CIRL Framework
Ryan Carey
A value learning system has incentives to follow shutdown instructions, assuming the shutdown instruction provides information (in the technical sense) about which actions lead to…