This paper outlines a preliminary perspective on teamwork and adjustable autonomy in groups involving a mix of humans and autonomous agents. Unlike other approaches to agent teamwork, a humancentered perspective to human-agent interaction is used. The paper describes how we are integrating the Brahms and KAoS agent frameworks in order to model and simulate realistic work situations in space and to support the design of robotic and software agents for human-agent teamwork.

We have developed a model-based, distributed architecture that integrates diverse components in a system designed for lunar and planetary surface operations: an astronaut’s space suit, cameras, all-terrain vehicles, robotic assistant, crew in a local habitat, and mission support team. Software processes (“agents”) implemented in the Brahms language, run on multiple, mobile platforms. These “mobile agents ” interpret and transform available data to help people and robotic systems coordinate their actions to make operations more safe and efficient. The Brahms-based mobile agent architecture (MAA) uses a novel combination of agent types so the software agents may understand and facilitate communications between people and between system components. A state-of-the-art spoken dialogue interface is integrated with Brahms models, supporting a speech-driven field observation record and rover command system. An important aspect of the methodology involves first simulating the entire system in Brahms, then configuring the agents into a runtime system Thus, Brahms provides a language, engine, and system builder’s toolkit for specifying and implementing multiagent systems. Background Multiagent systems were a natural outgrowth of knowledge-based systems of the 1970s, the idea of multiple, distributed sources of information and modelbased processing (“distributed AI”) developed in the 1980s, and the affordable, networked computing platforms of the 1990s. However, just as it has become practical to construct interacting systems of hardware and software, such as robotic assistants, GPS devices, biosensors, cameras, and the like, system builders need tools to help specify how these components are to interact in complex situations, means to test the designed processes, and an implementation architecture that is robust, modular, and amenable to runtime modifications (e.g., allowing components to leave or enter the system). We need a principled methodology for building multiagent systems (Alonso 2002). This paper describes how the Brahms simulation system

Because ever more powerful intelligent agents will interact with people in increasingly sophisticated and important ways, greater attention must be given to the technical and social aspects of how to make agents acceptable to people [87]. The technical challenge is to devise a computational structure that guarantees that from

Work system analysis and design is complex and nondeterministic. In this paper we describe Brahms, a multiagent modeling and simulation environment for designing complex interactions in human--machine systems. Brahms was originally conceived as a business process design tool that simulates work practices, including social systems of work. We describe our modeling and simulation method for mission operations work systems design, based on a research case study in which we used Brahms to design mission operations for a proposed discovery mission to the Moon. We then describe the results of an actual method application project---the Brahms Mars Exploration Rover. Space mission operations are similar to operations of traditional organizations; we show that the application of Brahms for space mission operations design is relevant and transferable to other types of business processes in organizations.

Abstract—A human-centered approach to computer systems design involves reframing analysis in terms of the people interacting with each other. The primary concern is not how people can interact with computers, but how shall we design work systems (facilities, tools, roles, and procedures) to help people pursue their personal projects, as they work independently and collaboratively? Two case studies provide empirical requirements. First, an analysis of astronaut interactions with CapCom on Earth during one traverse of Apollo 17 shows what kind of information was conveyed and what might be automated today. A variety of agent and robotic technologies are proposed that deal with recurrent problems in communication and coordination during the analyzed traverse. Second, an analysis of biologists and a geologist working at Haughton Crater in the High Canadian Arctic reveals how work interactions between people involve independent personal projects, sensitively coordinated for mutual benefit. In both cases, an agent or robotic system’s role would be to assist people, rather than collaborating, because today’s computer systems lack the identity and purpose that consciousness provides. Index Terms—Collaborative work, robots, model-based systems, field science, assistants, consciousness

We have developed and tested an advanced EVA communications and computing system to increase astronaut self-reliance and safety, reducing dependence on continuous monitoring and advising from mission control on Earth. This system, called Mobile Agents (MA), is voice controlled and provides information verbally to the astronauts through programs called “personal agents. ” The system partly automates the role of CapCom in Apollo—including monitoring and managing EVA navigation, scheduling, equipment deployment, telemetry, health tracking, and scientific data collection. EVA data are stored automatically in a shared database in the habitat/vehicle and mirrored to a site accessible by a remote science team. The program has been developed iteratively in the context of use, including six years of ethnographic observation of field geology. Our approach is to develop automation that supports the human work practices, allowing people to do what they do well, and to work in ways they are most familiar. Field experiments in Utah have enabled

... level that individual work practice—collaboration, communication, ‘off-task ’ behaviors, multi-tasking, interrupted and resumed activities, informal interactions, use of tools and movements—is left out, making the description of how the work in an organization actually gets done impossible. This paper describes the Brahms modeling and simulation environment, developed at NASA Ames Research Center. The Brahms modeling language is geared towards modeling people’s activity behavior, making it an ideal environment for simulating organizational processes at a level that allows the analysis of the work practice and designing new work processes at the implementation level.

analog sites for understanding planetary features and for training astronauts to be scientists. More recently, computer scientists and human factors specialists have followed geologists and biologists into the field, learning how science is actually done on expeditions in extreme environments. Research stations have been constructed by the Mars Society in the Arctic and American southwest, providing facilities for hundreds of researchers to investigate how small crews might live and work on Mars. Combining these interests—science, operations, and technology—in Mars analog field expeditions provides tremendous synergy and authenticity to speculations about Mars missions. By relating historical analyses of Apollo and field science, engineers are creating experimental prototypes that provide significant new capabilities, such as a computer system that automates some of the functions of Apollo’s CapCom. Thus, analog studies have created a community of practice—a new collaboration between scientists and engineers—so that technology begins with real human needs and works incrementally towards the challenges of the human exploration of Mars.

In the legal domain, ontologies enjoy quite some reputation as a way to model normative knowledge about laws and jurisprudence. Several methods have been used and are well-known qua ontological methods. However, no previous attempt to construct ontologies based on professional knowledge exists, capturing judicial practical expertise. This paper shows the preliminary ontology development for the second version of the prototype Iuriservice, a web based intelligent FAQ for judicial use, containing a repository of professional judicial knowledge. The iFAQ system will focus on such knowledge and will base on OPLK —Ontology of Professional Legal Knowledge — developed by UAB. Profesional Legal Knowledge refers to the core of professional work that contains the experience of the daily treatment of cases and is unevenly distributed within individuals as a result of their professional and personal experiences. The knowledge acquisition process has been based on an ethnographic process designed by the UAB team and the Spanish School of the Judiciary within the national SEC project, to efficiently obtain useful and representative information from questionnaire-based interviews. Nearly 800 competency questions have been extracted from these interviews and the ontology is being modelled from the selection of relevant terms. Regarding ontology modelling issues, we have followed the DILIGENT argumentation methodology to control the discussion and trace the arguments used in favor or against the introduction of a concept X as part of the domain ontology. This paper presents the preliminary Ontology of Professional Judicial Knowledge (OPJK) that has been extracted manually from the selection of relevant terms from nearly 200 competency questions and affirms that the modelling of this professional judicial knowledge demands the description of this knowledge as it is perceived by the judge and the abandonment of dogmatic legal categorizations. 1.

A model-based, distributed architecture integrates diverse components in a system designed for lunar and planetary surface operations: spacesuit biosensors, cameras, GPS, and a robotic assistant. The system transmits data and assists communication between the extra-vehicular activity (EVA) astronauts, the crew in a local habitat, and a remote mission support team. Software processes (“agents”), implemented in a system called Brahms, run on multiple, mobile platforms, including the spacesuit backpacks, all-terrain vehicles, and robot. These “mobile agents ” interpret and transform available data to help people and robotic systems coordinate their actions to make operations more safe and efficient. Different types of agents relate platforms to each other (“proxy agents”), devices to software (“comm agents”), and people to the system (“personal agents”). A state-of-the-art spoken dialogue interface enables people to communicate with their personal agents, supporting a speech-driven navigation and scheduling tool, field observation record, and rover command system. An important aspect of the engineering methodology involves first simulating the entire hardware and software system in Brahms, and then configuring the agents into a runtime system. Design of mobile agent functionality has been based on ethnographic observation of scientists working in Mars analog settings in the High Canadian Arctic on Devon Island and the southeast Utah desert (Clancey 2002a). The Mobile Agents system is developed iteratively in the context of use, with people doing authentic work. This paper provides a brief introduction to the architecture and emphasizes the method of empirical requirements analysis, through which observation, modeling, design, and testing are integrated in simulated EVA operations.