This paper presents an autonomous intelligent agent developed for monitoring Alzheimer patients' health care in execution time in geriatric residences. The AGALZ (Autonomous aGent for monitoring ALZheimer patients) is an autonomous deliberative casebased planner agent designed to plan the nurses' working time dynamically, to maintain the standard working reports about the nurses' activities, and to guarantee that the patients assigned to the nurses are given the right care. The agent operates in wireless devices and is integrated with complementary agents into a multi-agent system, named ALZ-MAS (ALZheimer Multi-Agent System), capable of interacting with the environment. AGALZ description, its relationship with the complementary agents, and preliminary results of the multi-agent system prototype in a real environment are presented.

This paper presents the SHOMAS multiagent system that provides guidance on leisure facilities and suggestions for shopping in malls. The multiagent architecture incorporates reactive and deliberative agents that take decisions automatically. This paper presents a deliberative agent that provides suggestions in execution time, with the help of case-based planners. This agent is described together with its guidance and suggestion mechanism. SHOMAS has been tested successfully, and the results obtained are presented in this paper.

Keywords:Case-based planning Case-based reasoning RFID Health care RPTW neural network a b s t r a c t This paper presents an intelligent environment developed for monitoring patients' health care in execution time in hospital environments. The CBPMP (case-based planner for monitoring patients) is an autonomous deliberative case-based planner designed to plan the nurses' working time dynamically, to maintain the standard working reports about the nurses' activities, and to guarantee that the patients assigned to the nurses are given the right care. The planner operates in wireless devices and is integrated with complementary software into an intelligent environment, named AmI-P (Ambient Intelligence for patients). CBPMP description, its relationship with the complementary technology, and preliminary results of system prototype in a real environment are presented.

This paper proposes a replanning mechanism for deliberative agents as a new approach to tackling the frame problem. We propose a beliefs desires and intentions (BDI) agent architecture using a case-based planning (CBP) mechanism for reasoning. We discuss the characteristics of the problems faced with planning where constraint satisfaction problems (CSP) resources are limited and formulate, through variation techniques, a reasoning model agent to resolve them. The design of the agent proposed, named MRP-Ag (most-replanable agent), will be evaluated in different environments using a series of simulation experiments, comparing it with others such as E-Ag (Efficient Agent) and O-Ag (Optimum Agent). Last, the most important results will be summarized, and the notion of an adaptable agent will be introduced.

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