Showing papers by "Hector J. Levesque published in 2000"

The logic of knowledge bases

Abstract: The idea of knowledge bases lies at the heart of symbolic, or "traditional," artificial intelligence. A knowledge-based system decides how to act by running formal reasoning procedures over a body of explicitly represented knowledge -- a knowledge base. The system is not programmed for specific tasks; rather, it is told what it needs to know and expected to infer the rest. This book is about the logic of such knowledge bases. It describes in detail the relationship between symbolic representations of knowledge and abstract states of knowledge, exploring along the way the foundations of knowledge, knowledge bases, knowledge-based systems, and knowledge representation and reasoning. Assuming some familiarity with first-order predicate logic, the book offers a new mathematical model of knowledge that is general and expressive yet more workable in practice than previous models. The book presents a style of semantic argument and formal analysis that would be cumbersome or completely impractical with other approaches. It also shows how to treat a knowledge base as an abstract data type, completely specified in an abstract way by the knowledge-level operations defined over it.

The adaptive agent architecture: achieving fault-tolerance using persistent broker teams

Abstract: Brokered multi-agent systems can be incapacitated and rendered non-functional when the brokers become inaccessible due to failures that can occur in any distributed software system. We propose that the theory of teamwork can be used to specify robust brokered architectures that can recover from broker failures, and we present the adaptive agent architecture (AAA) to show the feasibility of this approach. The previous teamwork theory based on joint intentions assumes that team members remain in a team as long as the team exists. We extend this theory to allow dynamic broker teams whose members can change with time. We also introduce a theory of restorative maintenance goals that enables the brokers in an AAA broker team to start new brokers and recruit them to the broker team. As a result, an AAA-based multi-agent system can maintain a specified number of functional brokers in the system despite broker failures, thus effectively becoming a self-healing system.

Iterated belief change in the situation calculus

Abstract: John McCarthy's situation calculus has left an enduring mark on artificial intelligence research. This simple yet elegant formalism for modelling and reasoning about dynamic systems is still in common use more than forty years since it was first proposed. The ability to reason about action and change has long been considered a necessary component for any intelligent system. The situation calculus and its numerous extensions as well as the many competing proposals that it has inspired deal with this problem to some extent. In this paper, we offer a new approach to belief change associated with performing actions that addresses some of the shortcomings of these approaches. In particular, our approach is based on a well-developed theory of action in the situation calculus extended to deal with belief. Moreover, by augmenting this approach with a notion of plausibility over situations, our account handles nested belief, belief introspection, mistaken belief, and handles belief revision and belief update together with iterated belief change.

Ability and knowing how in the situation calculus

Abstract: Most agents can acquire information about their environments as they operate A good plan for such an agent is one that not only achieves the goal, but is also executable, ie, ensures that the agent has enough information at every step to know what to do next In this paper, we present 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 Our account is more general than previous proposals, correctly handles programs containing loops, and incorporates a solution to the frame problem It can also be used to prove programs containing sensing actions correct

Designing the Semantics of Agent Communication Languages for Group Interaction

Abstract: Group communication is the core of societal interactions. Therefore, artificial agents should be able to communicate with groups as well as individuals. However, most contemporary agent communication languages, notably FIPA and KQML, have either no provision or no well-defined semantics for group communication. We give semantics for group communication that we believe can profitably enrich the agent communication languages. In our semantics, individual communication is a special case of group communication wherein each communicating group consists of a single agent.

Semantics of Agent Communication Languages for Group Interaction

Abstract: Group communication is the core of societal interactions Therefore, artificial agents should be able to communicate with groups as well as individuals However, most contem- porary agent communication languages, notably FIPA and KQML, have either no provision or no well-defined seman- tics for group communication We give a semantics for group communication that we believe can profitably enrich the agent communication languages In our semantics, indi- vidual communication is a special case of group communication wherein each communicating group consists of a single agent One of the novel features of this semantics is that it allows senders to send messages even without knowing all the potential recipients of those messages - a typical scenario in broadcast communication

An embedding of ConGolog in 3APL

Abstract: Several high-level programming languages for programming agents and robots have been proposed in recent years. Each of these languages has its own features and merits. It is still difficult, however, to compare different programming frameworks and evaluate the relative benefits and disadvantages of these frameworks. In this paper, we present a general method for comparing agent programming frameworks based on a notion of bisimulation, and use it to formally compare the languages ConGolog and 3APL.

Two approaches to efficient open-world reasoning

Abstract: We show how a simple but efficient evaluation procedure that is logically correct only for closed-world knowledge bases can nonetheless be used in certain contexts with open-world ones. We discuss two cases, one based on restricting queries to be in a certain normal form, and the other, arising in reasoning about actions, based on having sensing information at the right time so as to dynamically reduce open-word reasoning to closed-word reasoning.

Querying AOL Knowledge Bases

Abstract: For agents to behave successfully, they often need to reason about what they know and do not know about the world. For example, an agent may choose a particular sensing action only after it realizes that it is missing an important piece of information. From a knowledge representation point of view, the idea would be to supply the agent with a suitable knowledge base (KB) and provide it with an appropriate mechanism to query the KB. In order to get a glimpse of the complexity of the kinds of queries that might arise when actions are involved, let us consider the following example.