No abstract

Agent-oriented system development aims to simplify the construction of complex systems by introducing a natural abstraction layer on top of the object-oriented paradigm composed of autonomous interacting actors. One main advantage of the agent metaphor is that an agent can be described similar to the characteristics of the human mind consisting of several interrelated concepts which constitute the internal agent structure. General consensus exists that the Belief-Desire-Intention (BDI) model is well suited for describing an agent's mental state. The desires (goals) of an agent represent its motivational stance and are the main source for the agent's actions. Therefore, the representation and handling of goals play a central role in goal-oriented requirements analysis and modelling techniques. Nevertheless, currently available BDI agent platforms mostly abstract from goals and do not represent them explicitly. This leads to a gap between design and implementation with respect to the available concepts. In this paper a generic representation of goal types, properties, and lifecycles is developed in consideration of existing goal-oriented requirements engineering and modelling techniques. The objective of this proposal is to bridge the gap between agent specification and implementation of goals and is backed by experiences gained from developing a generic agent framework.

No abstract

No abstract

Abstract. One aspect of rational behavior is that agents can pursue multiple goals in parallel. Current BDI theory and systems do not provide a theoretical or architectural framework for deciding how goals interact and how an agent can decide which goals to pursue. Instead, they assume for simplicity reasons that agents always pursue consistent goal sets. By omitting this important aspect of rationality, the problem of goal deliberation is shifted from the architecture to the agent programming level and needs to be handled by the agent developer in an error-prone ad-hoc manner. In this paper a goal deliberation strategy called Easy Deliberation is proposed allowing agent developers to specify the relationships between goals in an easy and intuitive manner. It is based on established concepts from goal modeling as can be found in agent methodologies like Tropos and requirements engineering techniques like KAOS. The Easy Deliberation strategy has been realized within the Jadex BDI reasoning engine and is further explained by an example application. To fortify the practical usefulness of the approach it is experimentally shown that the computational cost for deliberation is acceptable and only increases polynomially with the number of concurrent goals.

Abstract. Multi-agent systems are a natural way of decomposing complex systems into more manageable and decentralized units. Nevertheless, as single agents can represent complex subsystems themselves, software engineering principles for the design and implementation of coherent parts of single agents are necessary for producing modular and reusable software artifacts. This paper picks up the formerly proposed capability concept for structuring BDI agents in functional clusters, and generalizes and extends it to support a higher degree of reusability. The resulting mechanism allows for designing and implementing BDI agents as a composition of configurable agent modules (capabilities). It is based on a black-box approach with export interfaces that is in line with objectoriented engineering principles.

More and more effort is made to provide methodologies for the development of agent-based systems. Awareness has grown that these are necessary to develop high quality agent systems. In recent years a number of proposals has been given. Based on our experiences we argue that a complete evaluation of methodologies cannot be done without considering target platforms, because the differences between available implementations are too fundamental to be ignored. In order to conduct a suitable comparison we present a flexible evaluation framework that takes platform specific criteria into account. Part of this framework is a procedure to derive relevant criteria from the evaluated platforms and methodologies. In combination with a set of platform dependent and independent criteria our framework allows evaluation of the appropriateness of methodologies with respect to platforms. As a consequence, also the suitability of methodologies for an individual platform, or vice versa of several platforms for an individual methodology can be examined. To show the usefulness of our proposal, we evaluate the suitability of different methodologies for an example platform.

Belief-Desire-Intention (BDI) agents are well suited for autonomous applications in dynamic environments. Their precompiled plan schemata contain the procedural knowledge of an agent and contribute to the performance. The agents generally are constrained to a fixed set of action patterns. Their choice depends on current goals, not on the future of the environment. Planning techniques can provide dynamic plans regarding the predicted state of the environment. We augment a BDI framework with a state-based planner for operational planning in domains where BDI is not well applicable. For this purpose, the requirements for the planner and for the coupling with a BDI system are investigated. An approach is introduced where a BDI system takes responsibility for plan monitoring and re-planning and the planner for the creation of plans. A fast state-based planner utilizing domain specific control knowledge retains the responsiveness of the system. In order to facilitate integration with BDI systems programmed in object-oriented languages, the planning problem is adopted into the BDI conceptual space with object-based domain models. The application of the hybrid system is illustrated using a propositional puzzle and a multi agent coordination scenario.