2 citations · 5 across the 9 of their papers we have counts for
9 papers
On Discovering Algorithms for Adversarial Imitation Learning
Shashank Reddy Chirra, Jayden Teoh, Praveen Paruchuri +1
Adversarial Imitation Learning (AIL) methods, while effective in settings with limited expert demonstrations, are often considered unstable. These approaches typically decompose in…
A Factored MDP Approach To Moving Target Defense With Dynamic Threat Modeling and Cost Efficiency
Megha Bose, Praveen Paruchuri, Akshat Kumar
Moving Target Defense (MTD) has emerged as a proactive and dynamic framework to counteract evolving cyber threats. Traditional MTD approaches often rely on assumptions about the at…
Preserving the Privacy of Reward Functions in MDPs through Deception
Shashank Reddy Chirra, Pradeep Varakantham, Praveen Paruchuri
Preserving the privacy of preferences (or rewards) of a sequential decision-making agent when decisions are observable is crucial in many physical and cybersecurity domains. For in…
Safety through feedback in Constrained RL
Shashank Reddy Chirra, Pradeep Varakantham, Praveen Paruchuri
In safety-critical RL settings, the inclusion of an additional cost function is often favoured over the arduous task of modifying the reward function to ensure the agent's safe beh…
City-scale Pollution Aware Traffic Routing by Sampling Max Flows using MCMC
Shreevignesh Suriyanarayanan, Praveen Paruchuri, Girish Varma
A significant cause of air pollution in urban areas worldwide is the high volume of road traffic. Long-term exposure to severe pollution can cause serious health issues. One approa…
Learning Effective Strategies for Moving Target Defense with Switching Costs
Vignesh Viswanathan, Megha Bose, Praveen Paruchuri
Moving Target Defense (MTD) has emerged as a key technique in various security applications as it takes away the attacker's ability to perform reconnaissance for exploiting a syste…
Multi-unit Double Auctions: Equilibrium Analysis and Bidding Strategy using DDPG in Smart-grids
Sanjay Chandlekar, Easwar Subramanian, Sanjay Bhat +2
Periodic double auctions (PDA) have applications in many areas such as in e-commerce, intra-day equity markets, and day-ahead energy markets in smart-grids. While the trades accomp…
How Private Is Your RL Policy? An Inverse RL Based Analysis Framework
Kritika Prakash, Fiza Husain, Praveen Paruchuri +1
Reinforcement Learning (RL) enables agents to learn how to perform various tasks from scratch. In domains like autonomous driving, recommendation systems, and more, optimal RL poli…
Bidding in Smart Grid PDAs: Theory, Analysis and Strategy (Extended Version)
Susobhan Ghosh, Sujit Gujar, Praveen Paruchuri +2
Periodic Double Auctions (PDAs) are commonly used in the real world for trading, e.g. in stock markets to determine stock opening prices, and energy markets to trade energy in orde…