research
∙
05/09/2023
Latent Interactive A2C for Improved RL in Open Many-Agent Systems
There is a prevalence of multiagent reinforcement learning (MARL) method...
share
research
∙
08/15/2022
IRL with Partial Observations using the Principle of Uncertain Maximum Entropy
The principle of maximum entropy is a broadly applicable technique for c...
research
∙
02/22/2022
SIPOMDPLite-Net: Lightweight, Self-Interested Learning and Planning in POSGs with Sparse Interactions
This work introduces sIPOMDPLite-net, a deep neural network (DNN) archit...
research
∙
09/16/2021
Marginal MAP Estimation for Inverse RL under Occlusion with Observer Noise
We consider the problem of learning the behavioral preferences of an exp...
research
∙
07/13/2021
A Hierarchical Bayesian model for Inverse RL in Partially-Controlled Environments
Robots learning from observations in the real world using inverse reinfo...
research
∙
06/17/2021
Many Agent Reinforcement Learning Under Partial Observability
Recent renewed interest in multi-agent reinforcement learning (MARL) has...
research
∙
10/15/2020
Cooperative-Competitive Reinforcement Learning with History-Dependent Rewards
Consider a typical organization whose worker agents seek to collectively...
research
∙
07/18/2020
Active Deception using Factored Interactive POMDPs to Recognize Cyber Attacker's Intent
This paper presents an intelligent and adaptive agent that employs decep...
research
∙
06/12/2020
Recurrent Sum-Product-Max Networks for Decision Making in Perfectly-Observed Environments
Recent investigations into sum-product-max networks (SPMN) that generali...
research
∙
04/27/2020
Maximum Entropy Multi-Task Inverse RL
Multi-task IRL allows for the possibility that the expert could be switc...
research
∙
11/20/2019
Scalable Decision-Theoretic Planning in Open and Typed Multiagent Systems
In open agent systems, the set of agents that are cooperating or competi...
research
∙
09/03/2019
GrAALF:Supporting Graphical Analysis of Audit Logs for Forensics
System-call level audit logs often play a critical role in computer fore...
research
∙
05/10/2019
SA-Net: Deep Neural Network for Robot Trajectory Recognition from RGB-D Streams
Learning from demonstration (LfD) and imitation learning offer new parad...
research
∙
06/18/2018
A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progress
Inverse reinforcement learning is the problem of inferring the reward fu...
research
∙
05/23/2018
Reinforcement Learning for Heterogeneous Teams with PALO Bounds
We introduce reinforcement learning for heterogeneous teams in which rew...
research
∙
05/21/2018
A Framework and Method for Online Inverse Reinforcement Learning
Inverse reinforcement learning (IRL) is the problem of learning the pref...
research
∙
10/27/2017
Inverse Reinforcement Learning Under Noisy Observations
We consider the problem of performing inverse reinforcement learning whe...
research
∙
07/14/2017
Freeway Merging in Congested Traffic based on Multipolicy Decision Making with Passive Actor Critic
Freeway merging in congested traffic is a significant challenge toward f...
research
∙
06/04/2017
Actor-Critic for Linearly-Solvable Continuous MDP with Partially Known Dynamics
In many robotic applications, some aspects of the system dynamics can be...
research
∙
11/13/2015
Dynamic Sum Product Networks for Tractable Inference on Sequence Data (Extended Version)
Sum-Product Networks (SPN) have recently emerged as a new class of tract...
research
∙
03/24/2015
Individual Planning in Agent Populations: Exploiting Anonymity and Frame-Action Hypergraphs
Interactive partially observable Markov decision processes (I-POMDP) pro...
research
∙
09/01/2014
Team Behavior in Interactive Dynamic Influence Diagrams with Applications to Ad Hoc Teams
Planning for ad hoc teamwork is challenging because it involves agents c...
research
∙
01/18/2014
Exploiting Model Equivalences for Solving Interactive Dynamic Influence Diagrams
We focus on the problem of sequential decision making in partially obser...
research
∙
01/15/2014