Extending Agent Languages for Autonomy

BDI agent languages provide a useful abstraction for complex systems comprised of interactive autonomous entities, but they have been used mostly in the context of single agents with a static plan library of behaviours invoked reactively. These languages provide a theoretically sound basis for agent design but are very limited in providing direct support for autonomy and societal cooperation needed for large scale systems. Some techniques for autonomy and cooperation have been explored in the past in ad hoc implementations, but not incorporated in any agent language. In order to address these shortcomings we extend the well known AgentSpeak(L) BDI agent language to include behaviour generation through planning, declarative goals and motivated goal adoption. We also develop a language-specific multiagent cooperation scheme and, to address potential problems arising from autonomy in a multiagent system, we extend our agents with a mechanism for norm processing leveraging existing theoretical work. These extensions allow for greater autonomy in the resulting systems, enabling them to synthesise new behaviours at runtime and to cooperate in non-scripted patterns.

A Framework for Monitoring Agent-Based Normative Systems

The behaviours of autonomous agents may deviate from those deemed to be for the good of the societal systems of which they are a part. Norms have therefore been proposed as a means to regulate agent behaviours in open and dynamic systems, where these norms specify the obliged, permitted and prohibited behaviours of agents. Regulation can effectively be achieved through use of enforcement mechanisms that result in a net loss of utility for an agent in cases where the agent's behaviour fails to comply with the norms. Recognition of compliance is thus crucial for achieving regulation. In this paper we propose a generic architecture for observation of agent behaviours, and recognition of these behaviours as constituting, or counting as, compliance or violation. The architecture deploys monitors that receive inputs from observers, and processes these inputs together with transition network representations of individual norms. In this way, monitors determine the fulfillment or violation status of norms. The paper also describes a proof of concept implementation and deployment of monitors in electronic contracting environments.

A Framework for Monitoring Agent-Based Normative Systems

The behaviours of autonomous agents may deviate from those deemed to be for the good of the societal systems of which they are a part. Norms have therefore been proposed as a means to regulate agent behaviours in open and dynamic systems, where these norms specify the obliged, permitted and prohibited behaviours of agents. Regulation can effectively be achieved through use of enforcement mechanisms that result in a net loss of utility for an agent in cases where the agent’s behaviour fails to comply with the norms. Recognition of compliance is thus crucial for achieving regulation. In this paper we propose a generic architecture for observation of agent behaviours, and recognition of these behaviours as constituting, or counting as, compliance or violation. The architecture deploys monitors that receive inputs from observers, and processes these inputs together with transition network representations of individual norms. In this way, monitors determine the fulfillment or violation status of norms. The paper also describes a proof of concept implementation and deployment of monitors in electronic contracting environments.

Evolutionary Testing of Autonomous Software Agents

A system built in terms of autonomous agents may require even greater correctness assurance than one which is merely reacting to the immediate control of its users. Agents make substantial decisions for themselves, so thorough testing is an important consideration. However, autonomy also makes testing harder; by their nature, autonomous agents may react in different ways to the same inputs over time, because, for instance they have changeable goals and knowledge. For this reason, we argue that testing of autonomous agents requires a procedure that caters for a wide range of test case contexts, and that can search for the most demanding of these test cases, even when they are not apparent to the agents’ developers. In this paper, we address this problem, introducing and evaluating an approach to testing autonomous agents that uses evolutionary optimization to generate demanding test cases.

Case studies for contract-based systems

Of the ways in which agent behaviour can be regulated in a multiagent system, electronic contracting – based on explicit representation of different parties' responsibilities, and the agreement of all parties to them – has significant potential for modern industrial applications. Based on this assumption, the CONTRACT project aims to develop and apply electronic contracting and contract-based monitoring and verification techniques in real world applications. This paper presents results from the initial phase of the project, which focused on requirements solicitation and analysis. Specifically, we survey four use cases from diverse industrial applications, examine how they can benefit from an agent-based electronic contracting infrastructure and outline the technical requirements that would be placed on such an infrastructure. We present the designed CONTRACT architecture and describe how it may fulfil these requirements. In addition to motivating our work on the contract-based infrastructure, the paper aims to provide a much needed community resource in terms of use case themselves and to provide a clear commercial context for the development of work on contract-based system.