activity
20182021
most citedLearning Human Rewards by Inferring Their Latent Intelligence Levels in Multi-Agent Games: A Theory-of-Mind Approach with Application to Driving Data

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.RO2021

Negotiation-Aware Reachability-Based Safety Verification for AutonomousDriving in Interactive Scenarios

Ran Tian, Anjian Li, Masayoshi Tomizuka +1

Safety assurance is a critical yet challenging aspect when developing self-driving technologies. Hamilton-Jacobi backward-reachability analysis is a formal verification tool for ve…

cs.AI20211 cited

Learning Human Rewards by Inferring Their Latent Intelligence Levels in Multi-Agent Games: A Theory-of-Mind Approach with Application to Driving Data

Ran Tian, Masayoshi Tomizuka, Liting Sun

Reward function, as an incentive representation that recognizes humans' agency and rationalizes humans' actions, is particularly appealing for modeling human behavior in human-robo…

cs.LG2020

Bounded Risk-Sensitive Markov Games: Forward Policy Design and Inverse Reward Learning with Iterative Reasoning and Cumulative Prospect Theory

Ran Tian, Liting Sun, Masayoshi Tomizuka

Classical game-theoretic approaches for multi-agent systems in both the forward policy design problem and the inverse reward learning problem often make strong rationality assumpti…

cs.AI2019

Beating humans in a penny-matching game by leveraging cognitive hierarchy theory and Bayesian learning

Ran Tian, Nan Li, Ilya Kolmanovsky +1

It is a long-standing goal of artificial intelligence (AI) to be superior to human beings in decision making. Games are suitable for testing AI capabilities of making good decision…

cs.GT2018

Adaptive Game-Theoretic Decision Making for Autonomous Vehicle Control at Roundabouts

Ran Tian, Sisi Li, Nan Li +3

In this paper, we propose a decision making algorithm for autonomous vehicle control at a roundabout intersection. The algorithm is based on a game-theoretic model representing the…