Complex, real-world domains require rethinking traditional approaches to AI planning.
Planning and executing the resulting plans in a dynamic environment implies a continual …

Constraint programming is a powerful paradigm for solving combinatorial search problems
that draws on a wide range of techniques from artificial intelligence, computer science …

We consider algorithmic problems in a distributed setting where the participants annot be
assumed to follow the algorithm but rather their own self-interest. As such pxticipants, termed …

The software world is one of great richness and diversity. Many thousands of software
products are available to users today, providing a wide variety of information and services in …

The long-term goal of our field is the creation and understanding of intelligence. Productive
research in AI, both practical and theoretical, benefits from a notion of intelligence that is …

A model for strategic negotiation for intelligent agents. As computers advance from isolated
workstations to linked elements in complex communities of systems and people, cooperation …

Automated negotiation and coalition formation among self-interested agents are playing an
increasingly important role in electronic commerce. Such agents cannot be coordinated by …

In a multi-agent environment, where self-motivated agents try to pursue their own goals,
cooperation cannot be taken for granted. Cooperation must be planned for and achieved …

Automated negotiation systems with self-interested agents are becoming increasingly
important. One reason for this is the technology push of a growing standardized …

In multiagent settings where the agents have different preferences, preference aggregation
is a central issue. Voting is a general method for preference aggregation, but seminal results …