Logical foundations of artificial intelligence
Logical foundations of artificial intelligence
Artificial Intelligence
Agents that reduce work and information overload
Communications of the ACM
AgentSpeak(L): BDI agents speak out in a logical computable language
MAAMAW '96 Proceedings of the 7th European workshop on Modelling autonomous agents in a multi-agent world : agents breaking away: agents breaking away
Foundations of distributed artificial intelligence
Structuring a Z Specification to Provide a Formal Framework for Autonomous Agent Systems
ZUM '95 Proceedings of the 9th International Conference of Z Usres on The Z Formal Specification Notation
From Agent Theory to Agent Construction: A Case Study
ECAI '96 Proceedings of the Workshop on Intelligent Agents III, Agent Theories, Architectures, and Languages
Formal Semantics for an Abstract Agent Programming Language
ATAL '97 Proceedings of the 4th International Workshop on Intelligent Agents IV, Agent Theories, Architectures, and Languages
A Formal Specification of dMARS
ATAL '97 Proceedings of the 4th International Workshop on Intelligent Agents IV, Agent Theories, Architectures, and Languages
Paradigma: Agent Implementation through Jini
DEXA '00 Proceedings of the 11th International Workshop on Database and Expert Systems Applications
A Logic Programming Language for Multi-agent Systems
JELIA '02 Proceedings of the European Conference on Logics in Artificial Intelligence
Agents, multi-agent systems and declarative programming: what, when, where, why, who, how?
A 25-year perspective on logic programming
About declarative semantics of logic-based agent languages
DALT'05 Proceedings of the Third international conference on Declarative Agent Languages and Technologies
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The notion of agents has provided a way of imbuing traditional computing systems with an extra degree of flexibility that allows them to be more resilient and robust in the face of more varied and unpredictable forms of interaction. One class of agents, typically called intelligent agents, represent their world symbolically according to their beliefs, have goals which need to be achieved, and adopt plans or intentions to achieve them. Now, one approach to building agents is to design a programming language whose semantics are based on some theory of rational or intentional agency and to program the desired behaviour of individual agents directly using mental attitudes. Such a technique is referred to as agent oriented programming. Arguably, the most innovative of these languages is 3APL (pronounced "triple-a-p-l") which supports the construction of intelligent agents for the development of complex systems through a set of intuitive concepts like beliefs, goals and plans. In this paper, we provide a Z specification of the programming language 3APL which provides a basis for implementation and also adds to a growing library of agent techniques and features.