Distributed approaches to negotiation have special privacy properties as main advantage over existing centralized /cryptographic techniques: The problem of an agent only has to be revealed according to the needs of the negotiation. After a negotiation has closed, the agents know how much they have

to provide an answer or answered "don't know"; by contrast, 17 percent of respondents refused to provide their earnings. How should a social scientist interpret answers to questions about global life satisfaction or happiness? After all, life satisfaction is neither a direct, verifiable

and their interconnections) and that the agent knows how to interact in all roles except the one it is learning (e.g. an agent learning to listen should know how to speak). This paper presents an algorithm for learning the structure of a hierarchical dynamical system representing the interaction protocol at various

task is coordinated by its own task (coordination) agent which interacts with related task agents by event passing. Realized as reactive agents, the task agents know how to react to state changes as well as to structural workflow changes so that workflow changes can be handled also in a decentralized

a formal account of what it means for an agent to know how to execute a plan and to be able to achieve a goal. Such a theory is a prerequisite for producing specifications of planners for agents that can acquire information at run time. It is also essential to account for cooperation among agents

or build brains from the bottom up, we try to understand or build intelligent behavior from the top down. In particular, we ask what an agent would need to know in order to behave intelligently, and what computational mechanisms could allow this knowledge to be made available to the agent as required

Beliefs have been formally modelled in the last decades using doxastic logics. The possible worlds model and its associated Kripke semantics provide an intuitive semantics for these logics, but they seem to commit us to model agents that are logically omniscient (they believe every classical

that, assuming that agents act under uncertainty in some states of the system, the notion of allowable strategy should be defined with some caution. Moreover, we demonstrate a subtle difference between an agent knowing that he has a suitable strategy and knowing the strategy itself. We also point out

virtual agents.

A long tradition in economic theory models economic policy decisions as solutions to optimization problems solved by rational and wellinformed agents: 1 a single policymaker minimizes a loss function subject to some constraints. Another body of literature models policy decisions as if they were