activity
20192022
most citedSafe Multi-Agent Reinforcement Learning via Shielding

30 citations · 34 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG20221 cited

Scheduling for Urban Air Mobility using Safe Learning

Surya Murthy, Natasha A. Neogi, Suda Bharadwaj

This work considers the scheduling problem for Urban Air Mobility (UAM) vehicles travelling between origin-destination pairs with both hard and soft trip deadlines. Each route is d…

cs.LG202130 cited

Safe Multi-Agent Reinforcement Learning via Shielding

Ingy Elsayed-Aly, Suda Bharadwaj, Christopher Amato +3

Multi-agent reinforcement learning (MARL) has been increasingly used in a wide range of safety-critical applications, which require guaranteed safety (e.g., no unsafe states are ev…

cs.RO2020

Near-Optimal Reactive Synthesis Incorporating Runtime Information

Suda Bharadwaj, Abraham P. Vinod, Rayna Dimitrova +1

We consider the problem of optimal reactive synthesis - compute a strategy that satisfies a mission specification in a dynamic environment, and optimizes a performance metric. We i…

cs.RO2019

Strategy Synthesis for Surveillance-Evasion Games with Learning-Enabled Visibility Optimization

Suda Bharadwaj, Louis Ly, Bo Wu +2

This paper studies a two-player game with a quantitative surveillance requirement on an adversarial target moving in a discrete state space and a secondary objective to maximize sh…

eess.SY20191 cited

Online Synthesis for Runtime Enforcement of Safety in Multi-Agent Systems

Dhananjay Raju, Suda Bharadwaj, Ufuk Topcu

A shield is attached to a system to guarantee safety by correcting the system's behavior at runtime. Existing methods that employ design-time synthesis of shields do not scale to m…

cs.AI2019

Reward-Based Deception with Cognitive Bias

Bo Wu, Murat Cubuktepe, Suda Bharadwaj +1

Deception plays a key role in adversarial or strategic interactions for the purpose of self-defence and survival. This paper introduces a general framework and solution to address…