5 papers
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…
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…
Program Synthesis for Non-Linear Real Arithmetic: Going Beyond Realizability
S. Akshay, Supratik Chakraborty, R. Govind +1
We study the problem of synthesizing programs from nonlinear real arithmetic (NRA) specifications. Existing techniques, such as syntax-guided synthesis (SyGuS), fail to synthesize…
Knowledge Compilation for Quantification in Alternating Automata
S. Akshay, Alfredo Cantarella, Supratik Chakraborty +2
We present a knowledge compilation approach for existential and universal quantification in alternating automata. Knowledge compilation transforms formulas into normal forms with s…
Omega-regular Verification and Control for Distributional Specifications in MDPs
S. Akshay, Ouldouz Neysari, ÄorÄe ŽikeliÄ
A classical approach to studying Markov decision processes (MDPs) is to view them as state transformers. However, MDPs can also be viewed as distribution transformers, where an MDP…