This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
Abstract. This paper develops a local reasoning method to check lineartime temporal properties of concurrent programs. In practice, it is often infeasible to model check over the p...
This paper advocates a strict compositional and hybrid approach for obtaining key (performance) metrics of embedded At its core the developed methodology abstracts system componen...
Abstract. In this paper we analyze the recently proposed light-weight block cipher PRINTCipher. Applying algebraic methods and SAT-solving we are able to break 8 rounds of PRINTCip...