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Tien Mai

9 accepted papers

2026

Beyond Homogeneous Adversaries: Stackelberg Security Games with Mixed Quantal Response

IJCAI 2026

The quantal response (QR) model is widely used in Stackelberg security games (SSGs) to capture boundedly rational adversaries. Existing work on SSGs under QR, however, almost exclusively assumes a homogeneous attacker population, ignoring heterogeneity in attacker preferences and rationality. We stu

Cited by 0Scholar
2026

DualCOIL: Offline Imitation Learning from Contrasting Demonstrations

ICML 2026poster

Offline imitation learning typically learns from expert and unlabeled demonstrations, yet often overlooks the valuable signal in explicitly undesirable behaviors. In this work, we study offline imitation learning from contrasting behaviors, where the dataset contains both expert and undesirable demo…

Cited by 0SourceScholar
2026

Revisiting Distribution Correction Estimation for Offline Imitation Learning with Suboptimal Dataset

ICML 2026poster

Imitation Learning (IL) has demonstrated strong capabilities in learning high-quality policies from expert demonstrations for sequential decision-making tasks. Nonetheless, its effectiveness is significantly constrained in low-expert-data regimes. To mitigate this issue, previous works introduce ``*…

Cited by 0SourceScholar
2024

Imitate the Good and Avoid the Bad: An Incremental Approach to Safe Reinforcement Learning

AAAI 2024technical

A popular framework for enforcing safe actions in Reinforcement Learning (RL) is Constrained RL, where trajectory based constraints on expected cost (or other cost measures) are employed to enforce safety and more importantly these constraints are enforced while maximizing expected reward. Most rece…

2024

Reward Penalties on Augmented States for Solving Richly Constrained RL Effectively

AAAI 2024technical

Constrained Reinforcement Learning employs trajectory-based cost constraints (such as expected cost, Value at Risk, or Conditional VaR cost) to compute safe policies. The challenge lies in handling these constraints effectively while optimizing expected reward. Existing methods convert such trajecto…

2024

Tackling Stackelberg Network Interdiction against a Boundedly Rational Adversary

IJCAI 2024poster

This work studies Stackelberg network interdiction games --- an important class of games in which a defender first allocates (randomized) defense resources to a set of critical nodes on a graph while an adversary chooses its path to attack these nodes accordingly. We consider a boundedly rational a…

Cited by 0SourcePDFScholar
2023

Securing Lifelines: Safe Delivery of Critical Services in Areas with Volatile Security Situation via a Stackelberg Game Approach

AAAI 2023technical

Vaccine delivery in under-resourced locations with security risks is not just challenging but also life threatening. The COVID pandemic and the need to vaccinate added even more urgency to this issue. Motivated by this problem, we propose a general framework to set-up limited temporary (vaccination)…

Cited by 1SourcePDFScholar
2022

Choices Are Not Independent: Stackelberg Security Games with Nested Quantal Response Models

AAAI 2022technical

The quantal response (QR) model is widely used in Stackelberg security games (SSG) to model a bounded rational adversary. The QR model is a model of human response from among a large variety of prominent models known as discrete choice models. QR is the simplest type of discrete choice models and do…

Cited by 2SourcePDFScholar