Special Issue on Multi-agent Systems (original) (raw)

Engineering AgentSpeak(L): a formal computational model

Journal of Logic and Computation, 1998

Perhaps the most successful agent architectures, and certainly the best known, are those based on the Belief-Desire-Intention (BDI) framework. Despite the wealth of research that has accumulated on both formal and practical aspects of this framework, however, there remains a gap between the formal models and the implemented systems. In this paper, we build on earlier work by R a o aimed at narrowing this gap, by d e v eloping a strongly-typed, formal, yet computational model of the BDI-based AgentSpeak(L) language. AgentSpeak(L) is a programming language, based on the Procedural Reasoning System (PRS) and the Distributed Multi-Agent Reasoning System (dMARS), which determines the behaviour of the agents it implements. In developing the model, we add to Rao's work, identify some omissions, and progress beyond the description of a particular language by giving a formal speci cation of a general BDI architecture that can be used as the basis for providing further formal speci cations of more sophisticated systems.

Domain-specific Modelling Language for Belief-Desire-Intention Software Agents

IET Software, vol. 12, no. 4, pp. 356-364, DOI: 10.1049/iet-sen.2017.0094, 2018

Development of software agents according to Belief-Desire-Intention (BDI) model usually becomes challenging due to autonomy, distributedness and openness of multi-agent systems (MAS). Hence, in this paper, a domain-specific modeling language (DSML), called DSML4BDI, is introduced to support development of BDI agents. The syntax of the language provides the design of agent components required for the construction of the system according to the specifications of BDI architecture. The implementation of designed MAS on Jason BDI platform is also possible via model-to-text transformations built in the DSML. The comparative evaluation results showed that a significant amount of artifacts required for the exact MAS implementation can be automatically achieved by employing DSML4BDI. Moreover, time needed for developing a BDI agent system from scratch can be reduced to one-third in case of using DSML4BDI. Finally, qualitative assessment, based on the developers' feedback, exposed how DSML4BDI facilitates development of BDI agents.

CTL AgentSpeak(L): A specification language for agent programs

Journal of Algorithms, 2009

This work introduces CT L AgentSpeak(L) , a logic to specify and verify expected properties of rational agents implemented in the AgentSpeak(L) agent oriented programming language. Our approach is similar to the classic BDICT L modal logic, used to reason about agents modelled in terms of belief (BEL), desires (DES), intentions (INTEND). A new interpretation for the temporal operators in CT L: next ( ), eventually (♦), until(U), inevitable(A), etc., is proposed in terms of the transition system induced by the operational semantics of AgentSpeak(L). The main contribution of the approach is a better understanding of the relation between the programming language and its logical specification, enabling us to proof expected or desired properties for any agent programmed in AgentSpeak(L), e.g., commitment strategies.

CASO: a framework for dealing with objectives in a constraint-based extension to AgentSpeak(L

2006

Incorporating constraints into a reactive BDI agent programming language can lead to better expressive capabilities as well as more efficient computation (in some instances). More interestingly, the use of constraint-based representations can make it possible to deal with explicit agent objectives (as distinct from agent goals) that express the things that an agent may seek to optimize at any given point in time. In this paper we extend the preliminary work of Ooi et.al in augmenting the popular Belief-Desire-Intention (BDI) language AgentSpeak(L) with constraint-handling capabilities. We present a slightly modified version of their proposal, in the form of the language CAS (Constraint AgentSpeak). We then extend CAS to form the language CASO (Constraint AgentSpeak with Objectives) to incorporate explicit objectives (represented as objective functions) and present techniques for performing option selection (selecting the best plan to use to deal with the current event) as well as intention selection. In both cases, we present parametric look-ahead techniques, i.e., techniques where the extent of look-ahead style deliberation can be adjusted.

A Formal Description Language for Multi-Agent Architectures

Lecture Notes in Computer Science, 2008

Multi-Agent Systems (MAS) constitute a highly promising software architectural approach for modern application domains such as peer-to-peer and ubiquitous computing, information retrieval, semantic web services or ebusiness. Unfortunately, despite considerable work in software architecture during the last decade, few research efforts have aimed at truly defining languages for designing such architectures. This paper identifies the foundations for an architectural description language (ADL) to specify multi-agent system architectures. We propose a set of system design concepts based on the BDI (beliefdesire-intention) agent model and existing classical ADLs. We conceptualize it with the Z specification language to capture a "core" model of structural and behavioural elements fundamental to an architecture description for BDI-MAS. We partially apply it on a data integration system example to illustrate our proposal.

The state of the art in agent communication languages

Knowledge and Information Systems, 2000

Like societies of humans, there is a need for agents in a multi-agent system to rely on one another, enlist the support of peers in order to solve complex tasks. Agents will be able to cooperate only through a meaningful communication language that can bear correctly their mental states and convey precisely the content of their messages. In search for the ideal agent communication language (ACL), several initiatives like the pioneering work of the Knowledge Sharing Effort and the Foundation for Intelligent Physical Agents (FIPA) are paving the way for a platform where all agents would be able to interact regardless of their implementation environment. ACL is a new field of study that could gain from a survey in expanding its application areas. For this purpose, we examine in this paper the state of the art in ACL design and suggest some principles for building a generalized ACL framework. We then evaluate some existing ACL models, and present the current issues in ACL research, and new perspectives.

On the formal semantics of speech-act based communication in an agent-oriented programming language

2007

Research on agent communication languages has typically taken the speech acts paradigm as its starting point. Despite their manifest attractions, speech-act models of communication have several serious disadvantages as a foundation for communication in artificial agent systems. In particular, it has proved to be extremely difficult to give a satisfactory semantics to speech-act based agent communication languages. In part, the problem is that speech-act semantics typically make reference to the "mental states" of agents (their beliefs, desires, and intentions), and there is in general no way to attribute such attitudes to arbitrary computational agents. In addition, agent programming languages have only had their semantics formalised for abstract, stand-alone versions, neglecting aspects such as communication primitives. With respect to communication, implemented agent programming languages have tended to be rather ad hoc. This paper addresses both of these problems, by giving semantics to speech-act based messages received by an AgentSpeak agent. AgentSpeak is a logic-based agent programming language which incorporates the main features of the PRS model of reactive planning systems. The paper builds upon a structural operational semantics to AgentSpeak that we developed in previous work. The main contributions of this paper are as follows: an extension of our earlier work on the theoretical foundations of AgentSpeak interpreters; a computationally grounded semantics for (the core) performatives used in speech-act based agent communication languages; and a well-defined extension of AgentSpeak that supports agent communication.