68 citations · 204 across the 19 of their papers we have counts for
9 papers · 1 filter
Exposing Surveillance Detection Routes via Reinforcement Learning, Attack Graphs, and Cyber Terrain
Lanxiao Huang, Tyler Cody, Christopher Redino +8
Reinforcement learning (RL) operating on attack graphs leveraging cyber terrain principles are used to develop reward and state associated with determination of surveillance detect…
Inverse Reinforcement Learning for Strategy Identification
Mark Rucker, Stephen Adams, Roy Hayes +1
In adversarial environments, one side could gain an advantage by identifying the opponent's strategy. For example, in combat games, if an opponents strategy is identified as overly…
A Systems Theory of Transfer Learning
Tyler Cody, Peter A. Beling
Existing frameworks for transfer learning are incomplete from a systems theoretic perspective. They place emphasis on notions of domain and task, and neglect notions of structure a…
Empirically Measuring Transfer Distance for System Design and Operation
Tyler Cody, Stephen Adams, Peter A. Beling
Classical machine learning approaches are sensitive to non-stationarity. Transfer learning can address non-stationarity by sharing knowledge from one system to another, however, in…
Graph Convolution Networks for Probabilistic Modeling of Driving Acceleration
Jianyu Su, Peter A. Beling, Rui Guo +1
The ability to model and predict ego-vehicle's surrounding traffic is crucial for autonomous pilots and intelligent driver-assistance systems. Acceleration prediction is important…
Multi-agent Inverse Reinforcement Learning for Certain General-sum Stochastic Games
Xiaomin Lin, Stephen C. Adams, Peter A. Beling
This paper addresses the problem of multi-agent inverse reinforcement learning (MIRL) in a two-player general-sum stochastic game framework. Five variants of MIRL are considered: u…
Comparison of Multi-agent and Single-agent Inverse Learning on a Simulated Soccer Example
Xiaomin Lin, Peter A. Beling, Randy Cogill
We compare the performance of Inverse Reinforcement Learning (IRL) with the relative new model of Multi-agent Inverse Reinforcement Learning (MIRL). Before comparing the methods, w…
Behavior Pattern Recognition using A New Representation Model
Qifeng Qiao, Peter A. Beling
We study the use of inverse reinforcement learning (IRL) as a tool for the recognition of agents' behavior on the basis of observation of their sequential decision behavior interac…
Inverse Reinforcement Learning with Gaussian Process
Qifeng Qiao, Peter A. Beling
We present new algorithms for inverse reinforcement learning (IRL, or inverse optimal control) in convex optimization settings. We argue that finite-space IRL can be posed as a con…