35 citations · 89 across the 43 of their papers we have counts for
3 papers · 2 filters
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…
EduQate: Generating Adaptive Curricula through RMABs in Education Settings
Sidney Tio, Dexun Li, Pradeep Varakantham
There has been significant interest in the development of personalized and adaptive educational tools that cater to a student's individual learning progress. A crucial aspect in de…
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…