A Knowledge Based Semantics of Messages

2004

Nowadays it is increasing the tendency of using agents on behalf of information systems in their interactions with other autonomous information systems. Moreover, there exists an actual interest on getting these interactions at a semantic level, that is, beyond the syntactic level interaction provided by the XML format standard. In this paper we present a mechanism that gives an step forward in the global goal of achieving a semantic interoperability among agents. The mechanism is based on ontological commitments on the classes of messages interchanged by agents of different information systems in an scenario where agents act in a sincere, helpful and liberal way. Furthermore those messages are considered as individuals of OWL classes, and we take advantage of the reasoning supporting OWL ontologies.

Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems - AAMAS '06, 2006

In this paper we illustrate how a role-based semantics for agent communication languages can embed the two main existing models of agent communication languages, respectively based on 'mental attitudes' and 'social commitments' semantics. These two models have been presented as incompatible approaches, but recently we illustrated for persuasion dialogues and using our normative multiagent systems framework, that they can be seen also as complimentary ones. Independently from our own multi-agent model, in this paper we illustrate for the speech act 'inform' how the role based semantics embeds the other two semantics.

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

A flexible communication protocol is necessary to build a decentralized multiagent system whose member agents are not coupled to each other's decision making. Information-based protocol languages capture a protocol in terms of causality and integrity constraints based on the information exchanged by the agents. Thus, they enable highly flexible enactments in which the agents proceed asynchronously and messages may be arbitrarily reordered. However, the existing semantics for such languages can produce a large number of protocol enactments, which makes verification of a protocol property intractable. This paper formulates a protocol semantics declaratively via inference rules that determine when a message emission or reception becomes enabled during an enactment, and its effect on the local state of an agent. The semantics enables heuristics for determining when alternative extensions of a current enactment would be equivalent, thereby helping produce parsimonious models and yiel...

2004

The missing of an appropriate semantics of agent communication languages is one of the most challenging issues of contemporary AI. Although several approaches to this problem exist, none of them is really suitable for dealing with agent autonomy, which is a decisive property of artificial agents. This paper introduces an observation-based approach to the semantics of agent communication, which combines benefits of the two most influential traditional approaches to agent communication semantics, namely the ...

Agreement Technologies, 2013

In this chapter we discuss how semantic technologies in general and specific Semantic Web standards in particular can contribute to the goal of achieving interoperability between independent, loosely coupled, heterogeneous, autonomous software components (i.e. agents) and for the realization of open interaction systems. In particular we will discuss how those technologies have been used for the definition of the semantics of agent communication languages, for the definition of norms and policies used to regulate interactions in open frameworks, and for defining efficient mechanisms for matching demands (i.e., content they need) to supplies (i.e., available content) in telecommunication networks. In particular regarding this last type of application we describe a techno-economic approach for solving the matching problem, by means of a multi-agent system representing an electronic marketplace. Its functionality is realized by applying a semantic-aware content discovery model with two-level filtering in order to finally recommend a ranked set of eligible content to the users in response to their requests. The filtering processes not only consider the semantic information associated with the available content, but also ratings regarding the actual performance of businesses that act as content providers as well as the prices paid by businesses for advertising their content.

2022 IEEE International Conference on Communications Workshops (ICC Workshops)

This article aims to provide a unified and technical approach to semantic information, communication, and their interplay through the lens of probabilistic logic. To this end, on top of the existing technical communication (TC) layer, we additionally introduce a semantic communication (SC) layer that exchanges logically meaningful clauses in knowledge bases. To make these SC and TC layers interact, we propose various measures based on the entropy of a clause in a knowledge base. These measures allow us to delineate various technical issues on SC such as a message selection problem for improving the knowledge at a receiver. Extending this, we showcase selected examples in which SC and TC layers interact with each other while taking into account constraints on physical channels. Index Terms-semantic information; semantic communication; information theory; probabilistic logic; semantic and technical communication interplay I. INTRODUCTION Communication systems have been significantly transformed over the last decades, yet the foundation of the underlying information and communication technology has been consistently laid by Shannon's theory [1]. In his theory, information is characterized as randomness in variables. This allows one to calculate the fundamental limit and performance of communication, and to design efficient compression and transmission schemes through noisy channels. Despite the success in this domain of technical communication (TC), since its introduction in 1948, Shannon theory's ignorance about the meanings of information [2] has long been tackled particularly in the field of the philosophy of information. Meanwhile, overcoming this limitation of Shannon theory has recently been regarded as one of the key enablers for the upcoming sixth generation (6G) communication systems [3]-[5]. To fill this void, it requires to develop a theory on meaningful information, i.e., semantic information, as well as a novel communication technology based on semantic information, i.e., semantic communication (SC). For SC, existing works can be categorized into model-free methods leveraging machine learning [4], and model-based approaches that quantify semantic information [6] or specify the emergence of meanings through communication [5]. Our work falls into the latter category in the hope of unifying our analysis on SC with the existing modelbased analysis on TC.

The paper proposes a novel approach to the semantics of communication of self-interested and autonomous agents in open systems. It defines the semantics of communicative acts primarily as the observable effect of their actual use in social encounters, and differs thus fundamentally from mentalistic and current objectivist approaches to the semantics of agent communication languages. Empirical communication semantics enables the designer of agent-oriented software applications as well as agents to reason about social structures on the level of dynamically formed expectations, which we consider to be a crucial capability especially for social reasoning within and about open systems with truly autonomous black-or gray-box agents.

2004

This paper presents a logic for reasoning about the explicit knowledge of agents who represent their knowledge as finite sets of logical formulae, and who can change their knowledge by reasoning and communicating. No assumptions about closure or consistency conditions on the sets, or about soundness or completeness of the reasoning mechanisms, are made. Traditional epistemic logic, based on modal logic, is not a good model for the explicit knowledge of such agents, among other things because of the logical omniscience problem. We are interested in agents who can make different choices about how to reason and communicate, and in reasoning about how the agents can use communication to achieve common goals. To this end, our logic is partly based on Alternating-time Temporal Logic. The resulting logic allows the expression of properties about an agent's reasoning mechanism on the form "the agent knows modus ponens (MP)"-meaning that the agent's reasoning mechanism can perform the reasoning steps described by MP. Instead of a common closure condition such as "if the agent knows both p and p → q, then he must also know q", the following holds in our logic: "if the agent knows p, p → q and MP, then he has a strategy to get to know q in the future".

2003

Abstract. Agent communication is one of the key issues in multi-agent systems. Traditional interprocess communication formalisms are usually considered insufficient for this purpose because of their lack of expressiveness; thus, in most proposals for multi-agent architectures, an Agent Communication Language (ACL) is designed to provide for agent communication. However, a universally accepted standard for ACLs is still missing.

Applied Ontology

There are two main traditions in defining a semantics for agent communication languages, based either on mental attitudes or on social commitments. These traditions, even if they share the idea of speech acts as operators with preconditions and effects, and agents playing roles like speaker and hearer, rely on completely distinct ontologies. Not only does the mental attitudes approach refer to concepts like belief, desire, goal or intention and is the social commitment approach based on the notion of commitment, but the two approaches also refer to distinct speech acts, distinct types of dialogue games, and so on. In this paper, we propose a common ontology for both approaches based on public mental attitudes attributed to roles. Public mental attitudes avoid the problems of mentalistic semantics, such as the unverifiability of private mental states, and they allow the reuse of the logics and implementations developed for FIPA compliant approaches. Moreover, a common ontology of communication primitives allows for the construction of agents participating to dialogues with both FIPA and social commitments compliant agents. The challenge of agent communication languages whose semantics is based on public mental attitudes, such as our rolebased semantics, is to define mappings from existing languages to the new one. In this paper we show how to map the two existing traditions to our role-based ontology of public mental attitudes and we show how it allows for a comparison. Moreover, to test the generality of our new ontology for agent communication languages, we show how to extend the social commitment approach to cope with persuasion dialogue too.