11 citations · 21 across the 19 of their papers we have counts for
20 papers
Sequential Decision Making in Stochastic Games with Incomplete Preferences over Temporal Objectives
Abhishek Ninad Kulkarni, Jie Fu, Ufuk Topcu
Ensuring that AI systems make strategic decisions aligned with the specified preferences in adversarial sequential interactions is a critical challenge for developing trustworthy A…
Privacy-preserving Nash Equilibrium Synthesis with Partially Ordered Temporal Objectives
Caleb Probine, Abhishek Kulkarni, Ufuk Topcu
Nash equilibrium is a central solution concept for reasoning about self-interested agents. We address the problem of synthesizing Nash equilibria in two-player deterministic games…
Nash Equilibrium in Games on Graphs with Incomplete Preferences
Abhishek N. Kulkarni, Jie Fu, Ufuk Topcu
Games with incomplete preferences are an important model for studying rational decision-making in scenarios where players face incomplete information about their preferences and mu…
Integrated Resource Allocation and Strategy Synthesis in Safety Games on Graphs with Deception
Abhishek N. Kulkarni, Matthew S. Cohen, Charles A. Kamhoua +1
Deception plays a crucial role in strategic interactions with incomplete information. Motivated by security applications, we study a class of two-player turn-based deterministic ga…
Preference-Based Planning in Stochastic Environments: From Partially-Ordered Temporal Goals to Most Preferred Policies
Hazhar Rahmani, Abhishek N. Kulkarni, Jie Fu
Human preferences are not always represented via complete linear orders: It is natural to employ partially-ordered preferences for expressing incomparable outcomes. In this work, w…
Automaton-Guided Curriculum Generation for Reinforcement Learning Agents
Yash Shukla, Abhishek Kulkarni, Robert Wright +2
Despite advances in Reinforcement Learning, many sequential decision making tasks remain prohibitively expensive and impractical to learn. Recently, approaches that automatically g…