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cs.AI2026
Entropy Objectives in Markov Decision Processes
S. Akshay, Raghav Goyal, Aditya Neeraje +1
We consider the problem of synthesizing control policies that enforce a concentration property on the state distributions of a stochastic system. We present a formalization of this…
cs.AI2026
Quantifying Sensitivity for Tree Ensembles: A symbolic and compositional approach
Ajinkya Naik, Chaitanya Garg, S. Akshay +2
Decision tree ensembles (DTE) are a popular model for a wide range of AI classification tasks, used in multiple safety critical domains, and hence verifying properties on these mod…
cs.AI2024
Certified Policy Verification and Synthesis for MDPs under Distributional Reach-avoidance Properties
S. Akshay, Krishnendu Chatterjee, Tobias Meggendorfer +1
Markov Decision Processes (MDPs) are a classical model for decision making in the presence of uncertainty. Often they are viewed as state transformers with planning objectives defi…