Abstract not found

We address the issues of semantics and conversations for agent communication languages and the Knowledge Query Manipulation Language (KQML) in particular. Based on ideas from speech act theory, we present a semantic description for KQML that associates "cognitive" states of the agent with the use of the language's primitives (performatives). Wehave used this approach to describe the semantics for the whole set of reserved KQML performatives. Building on

Speech act theory is important not only in Linguistics, but also in Computer Science. It has applications in Distributed Computing, Distributed Artificial Intelligence, Natural Language Processing, and Electronic Data Interchange protocols. While much research into speech acts has been done, one aspect of them that has largely been ignored is their semantics, i.e., their conditions of satisfaction. A formal semantics for speech acts is motivated and presented here that relates their satisfaction to the intentions, know-how, and actions of the participating agents. This makes it possible to state several potentially useful constraints on communication and provides a basis for checking their consistency. An earlier version of this paper was presented at the Second Meeting on the Mathematics of Language, Tarrytown, NY, May 1991. Some parts of this paper overlap with [23]. y This research was supported by the National Science Foundation (through grant # IRI-8945845 to the Center for Co...

Abstract not found

This paper is about the flow of inference between communicative intentions, discourse structure and the do- main during discourse processing. We augment a theory of discourse interpretation with a theory of distinct mental attitudes and reasoning about them, in order to provide an account of how the attitudes interact with reasoning about discourse structure.

Multiagent systems are of interest in several subareas of Cognitive Science and Artificial Intelligence, notably, autonomous agents, multiagent planning and action, discourse understanding, and cooperative work. I motivate and present a formal theory of the intentions of a multiagent system that analyzes them in terms of its internal organization, and the intentions of its member agents. This theory treats social structure directly in terms of the interactions among agents and does not attempt to reduce it to psychological concepts. It makes few assumptions about the architecture of agents and about the manner in which they interact. Thus it is intuitively plausible, can be described in a simple formal model, and is applicable to a large variety of multiagent systems. This theory is applied to an extended example, and some interesting variations are outlined.

Abstract. We present a modal logic called LIA (Logic of Intention and Attempt) in which we can reason about intention dynamics and intentional action execution. By exploiting the expressive power of LIA, we provide a formal analysis of the relation between intention and action and highlight the pivotal role of attempt in action execution. Besides, we deal with the problems of instrumental reasoning and intention persistence.

Abstract. Intelligent agents, invented in artificial intelligence (AI), are finding application in a number of traditional areas. Classical AI notions such as knowledge and intentions can serve as natural primitives for the specification of agents. However, in order for them to live up to their promise, these notions must be given rigorous definitions. We propose formal definitions for intentions, knowledge, and know-how in a general model of actions and time. Our definitions are conceptually simple and are designed to be modular, in the sense of being orthogonal to one another. Using these definitions, we are able to prove a success result for agents that is akin to the notion of liveness in traditional computing. Others have been able to prove similar results only with the support of rather strong additional assumptions. 1

. Rationality is a useful metaphor for understanding autonomous, intelligent agents. A persuasive view of intelligent agents uses cognitive primitives such as intentions and beliefs to describe, explain, and specify their behavior. These primitives are often associated with a notion of commitment that is internal to the given agent. However, at first sight, there is a tension between commitments and rationality. We show how the two concepts can be reconciled for the important and interesting case of limited, intelligent agents. We show how our approach extends to handle more subtle issues such as precommitments, which have previously been assumed to be conceptually too complex. We close with a proposal to develop conative policies as a means to represent commitments in a generic, declarative manner. 1 Introduction How can limited agents cope with a complex world? This is a question that has drawn much attention in the study of intelligent agents. As agents find application in an incre...

Semiotics is the formal doctrine of signs. Organizational Semiotics is a particular branch of Semiotics, concerned with understanding organizations as information systems. Information Systems ’ core concepts such as information and communication are very complex and ill-defined concepts, which should be analyzed in terms of more elementary notions such as semiotic signs. Business processes would then be seen as processes involving the creation, exchange and use of signs. Rejecting the existence of a totally objective reality, we adopt as our philosophical stance a radical relativistic model. In this model both human agents and artificial agents have a constructed knowledge about reality, which requires the agent active participation, and all knowledge is connected to a knowing agent. In this view, organizational activity becomes an information process based on the notion of responsible agent, and we propose a model that accommodates both the social dimension in organizational agents behavior and the relative autonomy that individual agents exhibit in organizations. The EDA (Epistemic-Deontic-Axiological) model, here proposed, enables the representation of agent informational states and simultaneously defines the conceptual communication framework. Agents use their knowledge (epistemic level) and take into account their obligations and authorizations (deontic level), which they may choose to accept or to violate, to decide what to do next, i.e. to define their goals. In the process they