Sequential decision-making problems with multiple objectives arise naturally in practice and
pose unique challenges for research in decision-theoretic planning and learning, which has …

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The
devices cooperate to monitor one or more physical phenomena within an area of interest …

There is growing interest in reducing building energy consumption through increased
sensor data and increased computational support for building controls. The goal of reduced …

While a number of algorithms for multiobjective reinforcement learning have been proposed,
and a small number of applications developed, there has been very little rigorous empirical …

Graph-based games are an important tool in computer science. They have applications in
synthesis, verification, refinement, and far beyond. We review graph-based games with …

We study and provide efficient algorithms for multi-objective model checking problems for
Markov Decision Processes (MDPs). Given an MDP, M, and given multiple linear-time (ω …

The model-checking approach was originally formulated for verifying qualitative properties
of systems, for example safety and liveness (see Chap. 2), and subsequently extended to …

Many real-world decision problems have multiple objectives. For example, when choosing a
medical treatment plan, we want to maximize the efficacy of the treatment, but also minimize …

We present a verification framework for analysing multiple quantitative objectives of systems
that exhibit both nondeterministic and stochastic behaviour. These systems are modelled as …

We consider partially observable Markov decision processes (POMDPs) with ω-regular
conditions specified as parity objectives. The class of ω-regular languages provides a robust …