The formalization of legislation and the development of computer systems to assist with legal problem solving provide a rich domain for developing and testing artificial-intelligence technology.
In this article we survey ambient intelligence (AmI), including its applications, some of the technologies it uses, and its social and ethical implications. The applications include AmI at home, care of the elderly, healthcare, commerce, and business, recommender systems, museums and tourist scenarios, and group decision making. Among technologies, we focus on ambient data management and artificial intelligence; for example planning, learning, event-condition-action rules, temporal reasoning, and agent-oriented technologies. The survey is not intended to be exhaustive, but to convey a broad range of applications, technologies, and technical, social, and ethical challenges.
A multiagent system may be thought of as an artificial society of autonomous software agents and we can apply concepts borrowed from welfare economics and social choice theory to assess the social welfare of such an agent society. In this paper, we study an abstract negotiation framework where agents can agree on multilateral deals to exchange bundles of indivisible resources. We then analyse how these deals affect social welfare for different instances of the basic framework and different interpretations of the concept of social welfare itself. In particular, we show how certain classes of deals are both sufficient and necessary to guarantee that a socially optimal allocation of resources will be reached eventually.
This thesis describes the theory, application and implementation of a new method, called the Consistency method, for checking integrity constraints in deductive databases. It also describes a new proof procedure that has been developed for this application.The Consistency method is suitable for general range-restricted deductive databases where the constraints can be arbitrary formulae of first order predicate logic, and the transactions consist of one or more updates. Each update is an addition, deletion or modification of a database fact or non-atomic rule, or an addition or deletion of an integrity constraint.The Consistency method is based on general purpose theorem-proving techniques. The new proof procedure is an extension of SLDNF, which is the underlying proof procedure of Prolog. This new proof procedure allows forward as well as backward reasoning, and incorporates the negation as failure rule, as well as additional inference rules for reasoning about implicit deletions.Backward reasoning is particularly suited to query evaluation, where the database is static but the queries change. Forward reasoning, on the other hand, is particularly suited to knowledge assimilation, one component of which is integrity checking, where the database changes, and it is necessary to investigate the consequences of these changes. Our integrity checking method, called the Consistency method, for reasons that will become clear in the next chapter, is designed for range-restricted deductive databases (defined formally in the next chapter), integrity constraints that are expressed as formulae of first order predicate logic, and transactions that consist of one or more updates. Each update may be an addition, deletion or modification of a fact or non-atomic rule, or an addition or deletion of an integrity constraint.Deductive databases are extensions of relational databases. Relational databases can be thought of as consisting only of facts. Deductive databases may contain general rules as well as facts. Thus deductive databases have more expressive power, and allow a better compaction of information. A large part of the most recent British Nationality Act, 9 for example, has been formalised as a deductive database and implemented in Prolog (Sergot, Sadri, et al [1986]). It would be very difficult, and quite unnatural to represent complex information such as legislation as a relational database.Integrity constraints are conditions that the database is expected to satisfy as it changes through time. They are intended to prevent erroneous or undesirable information entering the database. If a transaction violates the constraints, the integrity of the database can be recovered in a number of different ways. One or more updates in the transaction can be rejected, or alternatively, the database or even the constraints can be modified. The recovery may be undertaken autonomously by the database management system, or through interaction with the user.The following are some examples of integrity constraints expressed in first...
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