119 research outputs found

    The agent programming language meta-APL

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    Abstract. We describe a novel agent programming language, Meta-APL, and give its operational semantics. Meta-APL allows both agent programs and their associated deliberation strategy to be encoded in the same programming language. We define a notion of equivalence between programs written in different agent programming languages based on the notion of weak bisimulation equivalence. We show how to simulate (up to this notion of equivalence) programs written in other agent programming languages by programs of Meta-APL. This involves translating both the agent program and the deliberation strategy under which it is executed into Meta-APL.

    Logic-Based Specification Languages for Intelligent Software Agents

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    The research field of Agent-Oriented Software Engineering (AOSE) aims to find abstractions, languages, methodologies and toolkits for modeling, verifying, validating and prototyping complex applications conceptualized as Multiagent Systems (MASs). A very lively research sub-field studies how formal methods can be used for AOSE. This paper presents a detailed survey of six logic-based executable agent specification languages that have been chosen for their potential to be integrated in our ARPEGGIO project, an open framework for specifying and prototyping a MAS. The six languages are ConGoLog, Agent-0, the IMPACT agent programming language, DyLog, Concurrent METATEM and Ehhf. For each executable language, the logic foundations are described and an example of use is shown. A comparison of the six languages and a survey of similar approaches complete the paper, together with considerations of the advantages of using logic-based languages in MAS modeling and prototyping.Comment: 67 pages, 1 table, 1 figure. Accepted for publication by the Journal "Theory and Practice of Logic Programming", volume 4, Maurice Bruynooghe Editor-in-Chie

    Agent programming using defeasible argumentation for knowledgerepresentation and reasoning

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    In this work two declarative approaches based on the BDI theory are studied, an agent programming language 3APL and an agent architecture that uses defeasible argumentation for knowledge representation and reasoning. Based on that study and considering that in 3APL the knowledge representation language is not fixed, we will propose 3APL-DeLP where the agent knowledge is represented by a DeLP-program and the agent may reason with a defeasible argumentation formalism.Red de Universidades con Carreras en Informática (RedUNCI

    Agent programming in the cognitive era

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    It is claimed that, in the nascent ‘Cognitive Era’, intelligent systems will be trained using machine learning techniques rather than programmed by software developers. A contrary point of view argues that machine learning has limitations, and, taken in isolation, cannot form the basis of autonomous systems capable of intelligent behaviour in complex environments. In this paper, we explore the contributions that agent-oriented programming can make to the development of future intelligent systems. We briefly review the state of the art in agent programming, focussing particularly on BDI-based agent programming languages, and discuss previous work on integrating AI techniques (including machine learning) in agent-oriented programming. We argue that the unique strengths of BDI agent languages provide an ideal framework for integrating the wide range of AI capabilities necessary for progress towards the next-generation of intelligent systems. We identify a range of possible approaches to integrating AI into a BDI agent architecture. Some of these approaches, e.g., ‘AI as a service’, exploit immediate synergies between rapidly maturing AI techniques and agent programming, while others, e.g., ‘AI embedded into agents’ raise more fundamental research questions, and we sketch a programme of research directed towards identifying the most appropriate ways of integrating AI capabilities into agent programs

    Preferences of Agents in Defeasible Logic

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    We are interested in programming languages for cognitive agents with preferences. We define rule-based agent theories and inference procedures in defeasible logic, and in this setting we discuss patterns of agent behavior called agent types

    Programming Cognitive Agents in Defeasible Logic

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    Defeasible Logic is extended to programming languages for cognitive agents with preferences and actions for planning. We define rule-based agent theories that contain preferences and actions, together with inference procedures. We discuss patterns of agent types in this setting. Finally, we illustrate the language by an example of an agent reasoning about web-services

    Reasoning about agent deliberation

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    We present a family of sound and complete logics for reasoning about deliberation strategies for SimpleAPL programs. SimpleAPL is a fragment of the agent programming language 3APL designed for the implementation of cognitive agents with beliefs, goals and plans. The logics are variants of PDL, and allow us to prove safety and liveness properties of SimpleAPL agent programs under different deliberation strategies. We show how to axiomatize different deliberation strategies for SimpleAPL programs, and, for each strategy we consider, prove a correspondence between the operational semantics of SimpleAPL and the models of the corresponding logic. We illustrate the utility of our approach with an example in which we show how to verify correctness properties for a simple agent program under different deliberation strategies

    Agent programming using defeasible argumentation for knowledgerepresentation and reasoning

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    In this work two declarative approaches based on the BDI theory are studied, an agent programming language 3APL and an agent architecture that uses defeasible argumentation for knowledge representation and reasoning. Based on that study and considering that in 3APL the knowledge representation language is not fixed, we will propose 3APL-DeLP where the agent knowledge is represented by a DeLP-program and the agent may reason with a defeasible argumentation formalism.Red de Universidades con Carreras en Informática (RedUNCI
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