The majority of multi-agent system implementations aim to optimise agents' policies with
respect to a single objective, despite the fact that many real-world problem domains are …

In a world of electronic calendars, the prospect of intelligent, personalized time management
assistance seems a plausible and desirable application of AI. PTIME (Personalized Time …

This paper proposes incremental preference elicitation methods for multicriteria decision
making with a Choquet integral. The Choquet integral is an evaluation function that performs …

This paper addresses the problem of optimizing the transportation of disabled persons from
home to specialized centres or schools. It is modelled as a Dial-a-ride problem (DARP) …

In this article, we propose new algorithms for multi-objective coordination graphs (MO-
CoGs). Key to the efficiency of these algorithms is that they compute a convex coverage set …

Many real-world decision problems require making tradeoffs among multiple objectives.
However, in some cases, the relative importance of these objectives is not known when the …

Decision making is hard. It often requires reasoning about uncertain environments, partial
observability and action spaces that are too large to enumerate. In such tasks decision …

Multiobjective optimization is a central problem in a wide range of contexts, such as multi-
agent optimization and multicriteria decision support or decision under risk and uncertainty …

Many real-world decision problems require making trade-offs between multiple objectives.
However, in some cases, the relative importance of the objectives is not known when the …

In this thesis, we present a decision-theoretic framework for building decision support
systems that incrementally elicit preferences of individual users over multiattribute outcomes …