AUML protocols: from specification to detailed design

In this work, we show how AUML protocol specifications in the Prometheus methodology can be automatically propagated to the detailed design of the methodology by creating appropriate artefacts. The approach is general to all design methodologies that follow the BDI model of agents

Early detection of design faults relative to requirement specifications in agent-based models

Agent systems are used for a wide range of applications, and techniques to detect and avoid defects in such systems are valuable. In particular, it is desirable to detect issues as early as possible in the software development lifecycle. We describe a technique for checking the plan structures of a BDI agent design against the requirements models, specified in terms of scenarios and goals. This approach is applicable at design time, not requiring source code. A lightweight evaluation demonstrates that a range of defects can be found using this technique

Checking consistency of agent designs against interaction protocols for early-phase defect location

Multi-agent systems are increasingly being used in complex applications due to features such as autonomy, proactivity, exibility, robustness and social ability. However, these very features also make verifying multi-agent systems a challeng- ing task. In this paper, we propose a mechanism, including automated tool support, for early phase defect detection by comparing agent interaction speci cations with the detailed design of the agents participating in the interactions. The basic intuition of our approach is to extract sets of possi- ble traces from the agent design and to verify whether these traces conform to the protocol speci cations. Our approach is based on the Prometheus agent design methodology but is applicable to other similar methodologies. Our initial eval- uation shows that even simple protocols developed by rela- tively experienced developers are prone to defects, and our approach is successful in uncovering some of these defects

An Information Theoretic, Microfluidic-Based Single Cell Analysis Permits Identification of Subpopulations among Putatively Homogeneous Stem Cells

An incomplete understanding of the nature of heterogeneity within stem cell populations remains a major impediment to the development of clinically effective cell-based therapies. Transcriptional events within a single cell are inherently stochastic and can produce tremendous variability, even among genetically identical cells. It remains unclear how mammalian cellular systems overcome this intrinsic noisiness of gene expression to produce consequential variations in function, and what impact this has on the biologic and clinical relevance of highly ‘purified’ cell subgroups. To address these questions, we have developed a novel method combining microfluidic-based single cell analysis and information theory to characterize and predict transcriptional programs across hundreds of individual cells. Using this technique, we demonstrate that multiple subpopulations exist within a well-studied and putatively homogeneous stem cell population, murine long-term hematopoietic stem cells (LT-HSCs). These subgroups are defined by nonrandom patterns that are distinguishable from noise and are consistent with known functional properties of these cells. We anticipate that this analytic framework can also be applied to other cell types to elucidate the relationship between transcriptional and phenotypic variation

Propagating AUML protocols to detailed design

The interaction between agents is a key aspect of multi-agent systems. AUML sequence diagrams are commonly used to specify these interactions between agents in terms of interaction protocols. Whilst most of the popular agent oriented software engineering methodologies such as Prometheus, Tropos, O-MaSE, INGENIAS and GAIA support AUML protocol specifications in the design, the supportive tools do not provide any mechanisms for ensuring that the detailed design, and consequently the implementations, faithfully follow these protocols. In this paper, we show how AUML protocol specifications in the Prometheus methodology can be automatically propagated to the detailed design of the methodology by creating appropriate artefacts. The approach is general to all design methodologies that follow the BDI model of agents. We empirically show that the manual translation of protocols to the detailed design even for a simple AUML protocol can be a tedious and error-prone task for even relatively experienced users. The evaluation shows that our automated approach address these issues to a large extent

Robust execution of BDI agent programs by exploiting synergies between intentions

A key advantage the reactive planning approach adopted by BDI-based agents is the ability to recover from plan execution failures, and almost all BDI agent programming languages and platforms provide some form of failure handling mechanism. In general, these consist of simply choosing an alternative plan for the failed subgoal (e.g., JACK, Jadex). In this paper, we propose an alternative approach to recovering from execution failures that relies on exploiting positive interactions between an agent's intentions. A positive interaction occurs when the execution of an action in one intention assists the execution of actions in other intentions (e.g., by (re)establishing their preconditions). We have implemented our approach in a scheduling algorithm for BDI agents which we call SP. The results of a preliminary empirical evaluation of SP suggest our approach out-performs existing failure handling mechanisms used by state-of-the-art BDI languages. Moreover, the computational overhead of SP is modest

SP-MCTS-based intention scheduling for BDI agents

[No abstract available