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Introduction: Agents in Health Care
Abstract
Agent technology has become a leading area of research in AI and computer science and the focus of a number of major initiatives. One of these is the AgentCities project funded by the European Union 5thFramework research programme(http:// www. agentcities. org). AgentCities is a federation of specialist communities with a common interest in agents, one of which is concerned with health care. In this book, John Nealon and Toni Moreno have brought together an interesting set of papers that discuss the many practical issues that arise in trying to build agent applications in medicine. The papers are not simply focused on the health care domain however: they also succeed in raising a number of theoretical issues of wide relevance to the general field of agent research
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Cooperative clinical information systems (CCIS) are destined to become an invaluable tool for managing care processes in which a number of interrelated care tasks are performed by a network of cooperating agents. After introducing this important new domain, the key mechanisms and structures needed to support CCIS are detailed - a set of communication primitives are developed, the concept of agent commitment is described, the structures needed for reasoning about allocating tasks to appropriate agents are presented, and the mechanisms for managing change in the cooperating community are outlined.
The provision of medical care typically involves a number of individuals, located in a number of different institutions, whose decisions and actions need to be coordinated if the care is to be effective and efficient. To facilitate this decision making and to ensure the coordination process runs smoothly, the use of software support is becoming increasingly widespread. To this end, this paper describes an agent-based system that was developed to help manage the care process in real-world settings. The agents themselves are implemented using a layered architecture, called AADCare, which combines a number of AI and agent techniques: a symbolic decision procedure for decision making with incomplete and conflicting information, a concept of accountability for task allocation, the notions of commitments and conventions for managing coherent cooperation, and a set of communication primitives for interagent interaction. The utility of this approach is demonstrated through the development of an application prototype for the clinical process of cancer treatment.