Historic Perspective of Intelligent Agents Omankwu, Obinnaya Chinecherem, Nwagu, Chikezie Kenneth, and Inyiama, Hycient 1 Computer Science Department, Michael Okpara University of Agriculture, Umudike Umuahia, Abia State, Nigeria saintbeloved@yahoo.com 2 Computer Science Department, Nnamdi Azikiwe University, Awka Anambra State, Nigeria, Nwaguchikeziekenneth@hotmail.com 3 Electronics & Computer Engineering Department, Nnamdi Azikiwe University, Awka Anambra State, Nigeria. ABSTRACT A search on Google for the keywords “intelligent agents’ will return more than 330,000 hits; “multi-agent” returns almost double that amount as well as over 5,000 citations on www.citeseer.com. What is agent technology and what has led to its enormous popularity in both the academic and commercial worlds? Agent-based system technology offers a new paradigm for designing and implementing software systems. The objective of this tutorial is to provide an overview of agents, intelligent agents and multi-agent systems, covering such areas as: 1. what an agent is, its origins and what it does, 2. how intelligence is defined for and differentiates an intelligent agent from an agent, 3. how multi-agent systems coordinate agents with competing goals to achieve a meaningful result, and 4. how an agent differs from an object of a class or an expert system. Examples are presented of academic and commercial applications that employ agent technology. The potential pitfalls of agent development and agent usage are discussed. Keywords Agents, intelligent agents, multi-agent systems, artificial intelligence WHAT IS AN AGENT? Historical Context Artificial Intelligence (AI) and agent systems have been closely related over the last thirty years. AI is interested in studying the components of intelligence (e.g., the ability to learn, plan) while the study of agents deals with integrating these same components. This distinction may seem to imply that all the problems within AI must be solved in order to build an agent. But, as Oren Etzioni points out, this is not the case – ‘Intelligent agents are ninety-nine percent computer science and one percent AI’ (Etzioni, 1996). While AI techniques may be drawn upon to build agents, not all the capabilities are required by an agent and thus not all AI problems need be solved before building an agent. For example, the ability to learn may not be a desirable trait for an agent in some situations while it is certainly a component of AI. Between 1960 and 1990, AI witnessed a great deal of progress in many sub-areas such as knowledge representation and inference, machine learning, vision, robotics. In addition, various advancements in computer science and computing e.g., multitasking, distributed computing, communicating processes, real-time systems and communication networks made the design, implementation and deployment of agent based systems possible, at least in principle. The potential applications in distributed databases, mobile computing, information gathering, and collaborative computing that take advantage of these advances in AI and computer systems pose a strong argument for the development of intelligent agents and multi-agent systems. But is all this in touch with the reality? One need look no further than NASA’s Deep Space 1 (DS1) project where an artificial intelligence system was placed on board to plan and execute spacecraft activities. In contrast to remote control, this sophisticated set of computer programs acts as an agent of the operations team on board the spacecraft. Rather than requiring humans to do the detailed planning necessary to carry out desired tasks, Remote Agent will formulate its own plans, by combining the high level goals provided by the operations team with its detailed knowledge of both the condition of the spacecraft and how to control it. It then executes that plan, constantly monitoring its progress. If problems develop, Remote Agent in many cases will be able to fix them or work around them. If it is unable to find a fix or a work around, it can request help from its human counterparts. Remote Agent operated DS1 spacecraft during two experiments that began on May 17, 1999, when it ran the on-board computer more than 60,000,000 miles from Earth. The tests were a step toward robotic explorers of the 21st century that are less costly, more capable, and more independent from ground control. These intelligent agents can have the potential of making space exploration of the future more productive while staying within NASA’s limited budget. By transferring functions normally International Journal of Computer Science and Information Security (IJCSIS), Vol. 15, No. 7, July 2017 119 https://sites.google.com/site/ijcsis/ ISSN 1947-5500