Driving safety: enhancing communication between clients, constructors and designers

This paper, which stems from qualitative research undertaken by the CRC for Construction Innovation in the context of the development of a Guide to Best Practice for Safer Construction in the Australian construction industry, investigates the communication relationship between the client, designer and constructor, and identifies the conditions under which effective communication takes place. Previous research has made little headway with respect to putting into practice strategies that have the potential to improve communication between the client, designer and constructor. This paper seeks to address this ongoing problem. From analysis of client, designer and constructor interviews that form part of industry-selected case studies reflecting excellence in OHS, best-practice tools that have the potential to enhance multi-party communication between the client, designer and constructor are presented. This research also informs the development of workable implementation strategies

An interaction protocol for bidirectional deliberation on direct help in agent teamwork.

This thesis proposes a new interaction protocol for direct help in agent teamwork. It addresses design questions that may arise in practical systems development, and achieves higher teamwork performance impact than previous versions of the Mutual Assistance Protocol (MAP). Direct help, such as performing an action on teammate's behalf, is deliberated by team members as need arises, rather than imposed by team organization or centralized mechanisms. The deliberation can start with a request for help, or with an offer of help the two design principles have been embodied in two distinct versions of MAP. Based on their observed complementarity, we refine and combine them into a single protocol that leverages their individual advantages. Its novel features let an agent initiate help deliberation with request or offer, and also simultaneously provide and receive help. Simulation experiments demonstrate its team performance gains while varying the environment dynamism, agent resources, and communication costs. --Leaf i.The original print copy of this thesis may be available here: http://wizard.unbc.ca/record=b200687

Proactive communication in multi-agent teamwork

Sharing common goals and acting cooperatively are critical issues in multiagent teamwork. Traditionally, agents cooperate with each other by inferring others' actions implicitly or explicitly, based on established norms for behavior or on knowledge about the preferences or interests of others. This kind of cooperation either requires that agents share a large amount of knowledge about the teamwork, which is unrealistic in a distributed team, or requires high-frequency message exchange, which weakens teamwork efficiency, especially for a team that may involve human members. In this research, we designed and developed a new approach called Proactive Communication, which helps to produce realistic behavior and interactions for multiagent teamwork. We emphasize that multi-agent teamwork is governed by the same principles that underlie human cooperation. Psychological studies of human teamwork have shown that members of an effective team often anticipate the needs of other members and choose to assist them proactively. Human team members are also naturally capable of observing the environment and others so they can establish certain parameters for performing actions without communicating with others. Proactive Communication endows agents with observabilities and enables agents use them to track othersâ mental states. Additionally, Proactive Communication uses statistical analysis of the information production and need of team members and uses these data to capture the complex, interdependent decision processes between information needer and provider. Since not all these data are known, we use their expected values with respect to a dynamic estimation of distributions. The approach was evaluated by running several sets of experiments on a Multi- Agent Wumpus World application. The results showed that endowing agents with observability decreased communication load as well as enhanced team performance. The results also showed that with the support of dynamic distributions, estimation, and decision-theoretic modeling, teamwork efficiency were improved

A mutual assistance protocol for agent teamwork.

This thesis proposes a novel protocol for incorporating helpful behavior into multiagent teamwork. In the proposed protocol, call the Mutual Assistance Protocol (MAP), an agent can use its own abilities and resources to advance a subtask assigned to another agent. The helpful act is performed only when the two agents jointly determine that it is in the interest of the team. The underlying design principle is that each agent assesses the team impact of changes in its own local plan. The distributed decision is reached through a bidding sequence similar to the Contract Net Protocol. The helpful act may consist in performing an action or in granting resources. The advantages of MAP over protocols that use unilateral help decisions are demonstrated through simulation experiments, using varying levels of mutual awareness in the team, dynamic disturbance in the environment, communication costs, and computation costs. --P. ii.The original print copy of this thesis may be available here: http://wizard.unbc.ca/record=b175526

Ergonomists as designers: computational modelling and simulation of complex socio-technical systems

Contemporary ergonomics problems are increasing in scale, ambition, and complexity. Understanding and creating solutions for these multi-faceted, dynamic, and systemic problems challenges traditional methods. Computational modelling approaches can help address this methodological shortfall. We illustrate this potential by describing applications of computational modelling to: (1) teamworking within a multi-team engineering environment; (2) crowd behaviour in different transport terminals; and (3) performance of engineering supply chains. Our examples highlight the benefits and challenges for multi-disciplinary approaches to computational modelling, demonstrating the need for socio-technical design principles. Our experience highlights opportunities for ergonomists as designers and users of computational models, and the instrumental role that ergonomics can play in developing and enhancing complex socio-technical systems. Recognising the challenges inherent in designing computational models, we reflect on practical issues and lessons learned so that computational modelling and simulation can become a standard and valuable technique in the ergonomists’ toolkit

Realizing networks of proactive smart products

The sheer complexity and number of functionalities embedded in many everyday devices already exceed the ability of most users to learn how to use them effectively. An approach to tackle this problem is to introduce ‘smart’ capabilities in technical products, to enable them to proactively assist and co-operate with humans and other products. In this paper we provide an overview of our approach to realizing networks of proactive and co-operating smart products, starting from the requirements imposed by real-world scenarios. In particular, we present an ontology-based approach to modeling proactive problem solving, which builds on and extends earlier work in the knowledge acquisition community on problem solving methods. We then move on to the technical design aspects of our work and illustrate the solutions, to do with semantic data management and co-operative problem solving, which are needed to realize our functional architecture for proactive problem solving in concrete networks of physical and resource-constrained devices. Finally, we evaluate our solution by showing that it satisfies the quality attributes and architectural design patterns, which are desirable in collaborative multi-agents systems

Reasoning effectively under uncertainty for human-computer teamwork

As people are increasingly connected to other people and computer agents, forming mixed networks, collaborative teamwork offers great promise for transforming the way people perform their everyday activities and interact with computer agents. This thesis presents new representations and algorithms, developed to enable computer systems to function as effective team members in settings characterized by uncertainty and partial information. For a collaboration to succeed in such settings, participants need to reason about the possible plans of others, to be able to adapt their plans as needed for coordination, and to support each other's activities. Reasoning on general teamwork models accordingly requires compact representations and efficient decision-theoretic mechanisms. This thesis presents Probabilistic Recipe Trees, a probabilistic representation of agents' beliefs about the probable plans of others, and decision-theoretic mechanisms that use this representation to manage helpful behavior by considering the costs and utilities of computer agents and people participating in collaborative activities. These mechanisms are shown to outperform axiomatic approaches in empirical studies. The thesis also addresses the challenge that agents participating in a collaborative activity need efficient decision-making algorithms for evaluating the effects of their actions on the collaboration, and they need to reason about the way other participants perceive these actions. This thesis identifies structural characteristics of settings in which computer agents and people collaborate and presents decentralized decision-making algorithms that exploit this structure to achieve up to exponential savings in computation time. Empirical studies with human subjects establish that the utility values computed by this algorithm are a good indicator of human behavior, but learning can help to better understand the way these values are perceived by people. To demonstrate the usefulness of these teamwork capabilities, the thesis describes an application of collaborative teamwork ideas to a real-world setting of ridesharing. The computational model developed for forming collaborative rideshare plans addresses the challenge of guiding self-interested people to collaboration in a dynamic setting. The empirical evaluation of the application on data collected from the real-world demonstrates the value of collaboration for individual users and environment