2 citations · 2 across the 11 of their papers we have counts for
13 papers
Risk-Aware Input-Constrained Safe Intercept Guidance Against Multiple Moving Defenders
Praveen Kumar Ranjan, Abhinav Sinha, Yongcan Cao +2
This paper develops a risk-aware guidance law for an attacker to intercept a stationary target in the presence of multiple moving defenders while respecting the control input limit…
Inference-Time Policy Alignment for Fair Reinforcement Learning
Umer Siddique, Peilang Li, Conor Wallace +1
Deep reinforcement learning (RL) agents achieve strong performance by optimizing scalar reward functions. However, once deployed, the policies of these RL agents are often rigid an…
Learning Fair Pareto-Optimal Policies in Multi-Objective Reinforcement Learning
Umer Siddique, Peilang Li, Yongcan Cao
Fairness is an important aspect of decision-making in multi-objective reinforcement learning (MORL), where policies must ensure both optimality and equity across multiple, potentia…
Engagement-Zone-Aware Input-Constrained Guidance for Safe Target Interception in Contested Environments
Praveen Kumar Ranjan, Abhinav Sinha, Yongcan Cao
We address target interception in contested environments in the presence of multiple defenders whose interception capability is limited by finite ranges. Conventional methods typic…
ReCollab: Retrieval-Augmented LLMs for Cooperative Ad-hoc Teammate Modeling
Conor Wallace, Umer Siddique, Yongcan Cao
Ad-hoc teamwork (AHT) requires agents to infer the behavior of previously unseen teammates and adapt their policy accordingly. Conventional approaches often rely on fixed probabili…
Three-dimensional Integrated Guidance and Control for Leader-Follower Flexible Formation of Fixed Wing UAVs
Praveen Kumar Ranjan, Abhinav Sinha, Yongcan Cao
This paper presents a nonlinear integrated guidance and control (IGC) approach for flexible leader-follower formation flight of fixed-wing unmanned aerial vehicles (UAVs) while acc…
Safety-Critical Input-Constrained Nonlinear Intercept Guidance in Multiple Engagement Zones
Praveen Kumar Ranjan, Abhinav Sinha, Yongcan Cao
This paper presents an input-constrained nonlinear guidance law to address the problem of intercepting a stationary target in contested environments with multiple defending agents.…
Adaptive Event-Triggered Policy Gradient for Multi-Agent Reinforcement Learning
Umer Siddique, Abhinav Sinha, Yongcan Cao
Conventional multi-agent reinforcement learning (MARL) methods rely on time-triggered execution, where agents sample and communicate actions at fixed intervals. This approach is of…
TransAM: Transformer-Based Agent Modeling for Multi-Agent Systems via Local Trajectory Encoding
Conor Wallace, Umer Siddique, Yongcan Cao
Agent modeling is a critical component in developing effective policies within multi-agent systems, as it enables agents to form beliefs about the behaviors, intentions, and compet…
From Explainability to Interpretability: Interpretable Policies in Reinforcement Learning Via Model Explanation
Peilang Li, Umer Siddique, Yongcan Cao
Deep reinforcement learning (RL) has shown remarkable success in complex domains, however, the inherent black box nature of deep neural network policies raises significant challeng…
Adaptive Event-triggered Reinforcement Learning Control for Complex Nonlinear Systems
Umer Siddique, Abhinav Sinha, Yongcan Cao
In this paper, we propose an adaptive event-triggered reinforcement learning control for continuous-time nonlinear systems, subject to bounded uncertainties, characterized by compl…
3D Guidance Law for Flexible Target Enclosing with Inherent Safety
Praveen Kumar Ranjan, Abhinav Sinha, Yongcan Cao
In this paper, we address the problem of enclosing an arbitrarily moving target in three dimensions by a single pursuer while ensuring the pursuer's safety by preventing collisions…
Self-organizing Multiagent Target Enclosing under Limited Information and Safety Guarantees
Praveen Kumar Ranjan, Abhinav Sinha, Yongcan Cao
This paper introduces an approach to address the target enclosing problem using non-holonomic multiagent systems, where agents self-organize on the enclosing shape around a fixed t…