Abstract: Several approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a supervis...
Abstract--The difficulties encountered in sequential decisionmaking problems under uncertainty are often linked to the large size of the state space. Exploiting the structure of th...
We introduce an approach to autonomously creating state space abstractions for an online reinforcement learning agent using a relational representation. Our approach uses a tree-b...
Ensuring correctness of software by formal methods is a very relevant and widely studied problem. Automatic verification of software using model checkers from the state space exp...
Verification of programs requires reasoning about sets of program states. In case of programs manipulating pointers, program states are pointer graphs. Verification of such prog...