Using Conceptual Graphs to Represent Agent Semantic Constituents

Conceptual Structures in Practice, 2009

A conceptual graph (CG) is a graph representation for logic based on the semantic networks of artificial intelligence and the existential graphs of Charles Sanders Peirce. CG design principles emphasize the requirements for a cognitive representation: a smooth mapping to and from natural languages; an "iconic" structure for representing patterns of percepts in visual and tactile imagery; and cognitively realistic operations for perception, reasoning, and language understanding. The regularity and simplicity of the graph structures also support efficient algorithms for searching, pattern matching, and reasoning. Different subsets of conceptual graphs have different levels of expressive power: the ISO standard conceptual graphs express the full semantics of Common Logic (CL), which includes the subset used for the Semantic Web languages; a larger CG subset adds a context notation to support metalanguage and modality; and the research CGs are exploring an open-ended variety of extensions for aspects of natural language semantics. Unlike most notations for logic, CGs can be used with a continuous range of precision: at the formal end, they are equivalent to classical logic; but CGs can also be used in looser, less disciplined ways that can accommodate the vagueness and ambiguity of natural languages. This chapter surveys the history of conceptual graphs, their relationship to other knowledge representation languages, and their use in the design and implementation of intelligent systems.

1979

Conceptual graphs are both a language for representing knowledge and patterns for constructing models. They form models in the AI sense of structures that approximate some actual or possible system in the real world. They also form models in the logical sense of structures for which some set of axioms are true. When combined with recent developments in nonstandard logic and semantics, conceptual graphs can form a bridge between heuristic techniques of AI and formal techniques of model theory.

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.

Lecture Notes in Computer Science, 2007

In this paper we develop a semantics of our approach based on commitments and arguments for conversational agents. We propose a logical model based on CTL* (Extended Computation Tree Logic) and on dynamic logic. Called Commitment and Argument Network (CAN), our formal framework based on this hybrid approach uses three basic elements: social commitments, actions that agents apply to these commitments and arguments that agents use to support their actions. The advantage of this logical model is to gather all these elements and the existing relations between them within the same framework. The semantics we develop here enables us to reflect the dynamics of agent communication. It also allows us to establish the important link between commitments as a deontic concept and arguments. On the one hand CTL* enables us to express all the temporal aspects related to the handling of commitments and arguments. On the other hand, dynamic logic enables us to capture the actions that agents are committed to achieve.

Lecture Notes in Computer Science, 1998

Conceptual Graphs and Formal Concept Analysis are combined by developing a logical theory for concept graphs of relational contexts. Therefore, concept graphs are introduced as syntactical constructs, and their semantics is de ned based on relational contexts. For this contextual logic, a sound and complete system of inference rules is presented and a standard graph is introduced that entails all concept graphs being valid in a given relational context. A possible use for conceptual knowledge representation and processing is suggested.

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.

2007

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.

2009

Communication is key in a multi-agent system for agents to exchange information and coordinate their activities. In the area of agent programming, the challenge is to introduce communication primitives that are useful to a programmer of agent programs as well as semantically well-defined. Moreover, for agents that derive their choice of action from their beliefs and goals it is natural to introduce primitives that support communication related to both of these attitudes. We introduce a communication approach for multi-agent systems based on mood operators instead of the usual speech act labels and a semantics based on the idea that a message can be used to (re)construct a mental model of the sender. An operational semantics is provided that specifies the precise meaning of the primitives. Finally, to facilitate coordination in multi-agent systems, we introduce the concept of a conversation to synchronize actions and communication among agents. Conversations provide a limited resource at the multi-agent level, and provide a natural approach for multi-agent systems to coordinate agent activities.

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.

2007

Abstract Conceptual Graphs (CGs) are a visual, logic based knowledge representation (KR) formalism. In this paper we show how Conceptual Graph Assemblies (CGAs), a combinatorial extension to Conceptual Graphs, can represent multiple perspectives on the same information and enable the creation and use of modular and reusable CG representations.