Reasoning about preferences in BDI agent systems

BDI agents often have to make decisions about which plan is used to achieve a goal, and in which order goals are to be achieved. In this paper we describe how to incorporate preferences (based on the LPP language) into the BDI execution model

Prometheus design tool

The Prometheus Design Tool (PDT) supports the structured design of intelligent agent systems. It supports the Prometheus methodology, but can also be used more generally. This paper outlines the tool and some of its many features

Model based testing for agent systems

Although agent technology is gaining world wide popularity, a hindrance to its uptake is the lack of proper testing mechanisms for agent based systems. While many traditional software testing methods can be generalized to agent systems, there are many aspects that are different and which require an understanding of the underlying agent paradigm. In this paper we present certain aspects of a testing framework that we have developed for agent based systems. The testing framework is a model based approach using the design models of the Prometheus agent development methodology. In this paper we focus on unit testing and identify the appropriate units, present mechanisms for generating suitable test cases and for determining the order in which the units are to be tested, present a brief overview of the unit testing process and an example. Although we use the design artefacts from Prometheus the approach is suitable for any plan and event based agent system

Contextual question answering for the health domain

Studies have shown that natural language interfaces such as question answering and conversational systems allow information to be accessed and understood more easily by users who are unfamiliar with the nuances of the delivery mechanisms (e.g., keyword-based search engines) or have limited literacy in certain domains (e.g., unable to comprehend health-related content due to terminology barrier). In particular, the increasing use of the web for health information prompts us to reexamine our existing delivery mechanisms. We present enquireMe, which is a contextual question answering system that provides lay users with the ability to obtain responses about a wide range of health topics by vaguely expressing at the start and gradually refining their information needs over the course of an interaction session using natural language. enquireMe allows the users to engage in 'conversations' about their health concerns, a process that can be therapeutic in itself. The system uses community-driven question-answer pairs from the web together with a decay model to deliver the top scoring answers as responses to the users' unrestricted inputs. We evaluated enquireMe using benchmark data from WebMD and TREC to assess the accuracy of system-generated answers. Despite the absence of complex knowledge acquisition and deep language processing, enquireMe is comparable to the state-of-the-art question answering systems such as START as well as those interactive systems from TREC

AUML protocols and code generation in the Prometheus design tool

Prometheus is an agent-oriented software engineering methodology. The Prometheus Design Tool (PDT) is a software tool that supports a designer who is using the Prometheus methodology. PDT has recently been extended with two significant new features: support for Agent UML interaction protocols, and code generation

Eclipse-based prometheus design tool

The Prometheus Design Tool (PDT) is a graphical tool that is used to design a Multi-Agent System following the Prometheus Methodology. This paper describes the latest version of PDT which is now integrated into the Eclipse platform, enabling the users to accomplish the full development life-cycle of an agent-oriented application in one IDE and also inherit the rich set of product development features that Eclipse provides. This version of PDT also aims to support simpler integration with tools from other AOSE methodologies where appropriate

Health conversational system based on contextual matching of community-driven question-answer pairs

More and more people are turning to the World Wide Web for learning and sharing information about their health us- ing search engines, forums and question answering systems. In this demonstration, we look at a new way of deliver- ing health information to the end-users via coherent con- versations. The proposed conversational system allows the end-users to vaguely express and gradually refine their in- formation needs using only natural language questions or statements as input. We provide example scenarios in this demonstration to illustrate the inadequacies of current de- livery mechanisms and highlight the innovative aspects of the proposed conversational system

An improved approach to reinforcement learning in computer go

Monte-Carlo Tree Search (MCTS) has revolutionized, Computer Go, with programs based on the algorithm, achieving a level of play that previously seemed decades away., However, since the technique involves constructing a search tree, its performance t

Automated unit testing intelligent agents in PDT

The Prometheus Design Tool (PDT) is an agent development tool that supports the Prometheus design methodology and includes features like automated code generation. We enhance this tool by adding a feature that allows the automated unit testing of agents that are built from within PDT

Measuring plan coverage and overlap for agent reasoning

In Belief Desire Intention (BDI) agent systems it is usual for goals to have a number of plans that are possible ways of achieving the goal, applicable in di erent situations, usually captured by a context condition. In Agent Oriented Software Engineering it has been suggested that a designer should be conscious of whether a goal has complete coverage, that is, is there some plan that is applicable for every situation. Similarly a designer should be conscious of overlap, that is, for a given goal, are there situations where more than one plan could be applicable for achieving that goal. In this paper we further develop these notions in two ways, and then describe how they can be used both in agent reasoning and agent system development. Firstly we replace the boolean value for basic coverage and overlap with numerical measures, and explain how these may be calculated. Secondly we describe a measure that combines these basic measures, with the characteristics of the coverage/overlap in the goal-plan tree below a given goal. We then describe how these domain independent measures can be used for both plan selection and intention selection, as well as for guidance in agent system development