Howell R. Jordan

Evaluating agent-oriented programs: towards multi-paradigm metrics

Metrics are increasingly seen as important tools for software engineering and quantitative research, but little attention has so far been devoted to metrics for agent programming languages. This paper presents the first steps towards multi-paradigm structural metrics, which can be applied seamlessly to both agents and the object-oriented environments in which they are situated - thus enabling the designs of complete multi-agent systems to be quantitatively evaluated. Concrete paradigm-independent metrics for coupling and cohesion are proposed, and their use is demonstrated on an example Jason program, written in AgentSpeak and Java.

A Feature Model of Actor, Agent, Functional, Object, and Procedural Programming Languages

Abstract The number of programming languages is large and steadily increasing. However, little structured information and empirical evidence is available to help software engineers assess the suitability of a language for a particular development project or software architecture. We argue that these shortages are partly due to a lack of high-level, objective programming language feature assessment criteria: existing advice to practitioners is often based on ill-defined notions of ‘paradigms’ [3, p. xiii] and ‘orientation’, while researchers lack a shared common basis for generalisation and synthesis of empirical results. This paper presents a feature model constructed from the programmers perspective, which can be used to precisely compare general-purpose programming languages in the actor-oriented, agent-oriented, functional, object-oriented, and procedural categories. The feature model is derived from the existing literature on general concepts of programming, and validated with concrete mappings of well-known languages in each of these categories. The model is intended to act as a tool for both practitioners and researchers, to facilitate both further high-level comparative studies of programming languages, and detailed investigations of feature usage and efficacy in specific development contexts.

Evaluation of a Conversation Management Toolkit for Multi Agent Programming

The Agent Conversation Reasoning Engine (ACRE) is intended to aid agent developers to improve the management and reliability of agent communication. To evaluate its effectiveness, a problem scenario was created that could be used to compare code written with and without the use of ACRE by groups of test subjects. This paper describes the requirements that the evaluation scenario was intended to meet and how these motivated the design of the problem. Two experiments were conducted with two separate sets of students and their solutions were analysed using a combination of simple objective metrics and subjective analysis. The analysis suggested that ACRE by default prevents some common problems arising that would limit the reliability and extensibility of conversation-handling code. As ACRE has to date been integrated only with the Agent Factory multi agent framework, it was necessary to verify that the problems identified are not unique to that platform. Thus a comparison was made with best practice communication code written for the Jason platform, in order to demonstrate the wider applicability of a system such as ACRE.

Modelling software engineering research with RSML

Background. In order to understand research on a particular computing topic, practitioners and researchers often need to obtain an overview of its research methods. Current research methods coding schemes either capture insufficient details to support a full critical assessment, or are specialised to a particular research type. Aim. This paper defines and demonstrates RSML, a Research Schema Modelling Language that captures a high level of detail and is applicable to most types of computing research. Method. RSML was designed using concepts from the research methods literature, then refined inductively. An RSML editor was created to assist coders and help reduce coding errors. To demonstrate the feasibility of modelling research with RSML, and to exemplify the summary information that can be derived from a database of RSML encodings, a trial review of 24 articles from one journal was conducted. Results. The review illustrates quantitatively the journals focus on artifact construction and empiricism. It also reveals that observations are rarely used to inform artifact construction, and purely empirical studies are scarce. Conclusion. RSML can be used to model sophisticated, multifaceted research spanning a wide range of software engineering topics, yielding insights that are not easily captured by current coding schemes.

Reuse by Inheritance in Agent Programming Languages

The need to modularise and thereby reuse complex agent programs has long been recognised in agent programming language research. Current approaches to agent modularity fall into two main categories: compositional; and environment-based. Motivated by a problem which requires two variants of the same agent to be built, this paper proposes a set of language extensions which add a complementary modularity style - reuse by inheritance - to agent programming languages. The extensions are designed so that they can be implemented in a preprocessor and added easily to an existing language, without affecting its type system, and with little or no change to its underlying interpreter.

A feature model of actor, agent, and object programming languages

This paper presents first steps towards a feature model, which can be used to compare actor-oriented, agent-oriented, and object-oriented programming languages. The feature model is derived from the existing literature on general concepts of programming, and validated against Erlang, Jason, and Java. The model acts as a tool to assist practitioners in selecting the most appropriate programming language for a given task, and is expected to form the basis of further high-level comparative studies in this area.

AF-ABLE in the multi agent contest 2009

This is the second year in which a team from University College Dublin has participated in the Multi Agent Contest (http://www.multiagentcontest.org/2009). This paper describes the system that was created to participate in the contest, along with observations of the team’s experiences in the contest. The system itself was built using the AFAPL agent programming language running on the Agent Factory platform. A hybrid control architecture inspired by the SoSAA strategy aided in the separation of concerns between low-level behaviours (such as movement and obstacle evasion) and higher-level planning and strategy.

Separation of concerns in hybrid component and agent systems

This paper discusses the Socially Situated Agent Architecture (SoSAA) – a complete construction methodology that leverages existing well-established research and associated methodologies and frameworks in both the agent-oriented and component-based software engineering domains. As a software framework, SoSAA is intended to serve as a foundation on which to build agent-based applications by promoting separation of concerns in the development of open, heterogeneous, adaptive and distributed systems. The paper highlights concerns typically addressed in the development of distributed systems, such as adaptation, concurrency and fault-tolerance. It analyses how a hybrid agent/component integration approach can improve the separation of these concerns by leveraging modularity constructs already available in agent and component systems. Finally, it provides a first evaluation of the frameworks application by applying well-known metrics to a distributed information retrieval case study, and by discussing how these results can be projected to a typical multi-agent application developed with this hybrid approach.