In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinfo...
To model combinatorial decision problems involving uncertainty and probability, we introduce scenario based stochastic constraint programming. Stochastic constraint programs conta...
: This paper presents a fuzzy set based decision support model for taking uncertainty into account when making security investment decisions for distributed systems. The proposed m...
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
This paper proposes a stochastic dynamic thermal management (DTM) technique in high-performance VLSI system with especial attention to the uncertainty in temperature observation. ...