![]() For this purpose we omitted platforms that can no longer be used and we focused on platforms that are still available even if their development progress is stopped. Our intention was to include and examine the entire continuum of agent platforms that are available today. This article presents a comparative up-to-date review of the existing agent platforms. Moreover, in most cases surveys so far do not provide case classification, in other words the representatives are just described without indicating relations among them. However lately, people interested in using multi-agent systems in order to benefit from agent technology depend increasingly on solid survey articles.ġ.3 To date, in most cases multi-agent system surveys describe only some basic characteristics of a few representatives using a variety of criteria, which usually are different from survey to survey (e.g. With so many of them available, the choice of which one is best suited for each case was usually left to word of mouth, past experiences or platform publicity. All these platforms are as diverse as the community of people who use them. At the same time, the agent-oriented research community is still providing more and more new platforms. Some of them have already been abandoned whereas others continue releasing new versions. To this end, the research community has developed a variety of agent platforms in the last two decades either general purpose or oriented to a specific domain of use. Besides, a multi-agent system can be represented as a society, similar to a human society, consisting of entities with characteristics similar to humans, for instance in terms of autonomy and intelligence.ġ.2 However, although, intelligent agents have been around for years, their actual implementation is still in its early stages. Hence over time, multi-agent systems have been proven a really powerful tool for modelling and understanding phenomena in fields, such as economics and trading, health care, urban planning and social sciences. Many natural and artificial phenomena can be and in some cases they are represented by multi-agent systems. ![]() 2005 Sun & Naveh 2004 Kaminka 2004 Kubera et al. Actually, they can be used in numerous research areas, from computer games and informatics to economics and social sciences ( Schurr et al. Intelligent Agents, Multi-Agent Systems, Agent Platformsġ.1 Multi-agent systems can be used to investigate phenomena or solve problems that are difficult or impossible for humans to study and solve. It is based on universal comparison and evaluation criteria, proposing classifications for helping readers to understand which agent platforms broadly exhibit similar properties and in which situations which choices should be made. This article presents a comparative up-to-date review of the most promising existing agent platforms that can be used. To date, in most cases multi-agent system surveys describe only the basic characteristics of a few representatives without even providing any classification of the systems themselves. This decision was usually left to word of mouth, past experiences or platform publicity, lately however people depend on solid survey articles. ![]() Hence, a common problem is how people interested in using multi-agent systems should choose which platform to use in order to benefit from agent technology. This vast amount of platform options leads to a high degree of heterogeneity. On the other hand, the agent-oriented research community is still providing more and more new platforms. Since the late nineties many agent platforms have been developed. However, although, intelligent agents have been around for years, their actual implementation is still in its early stages. Over time, these systems have been proven a really powerful tool for modelling and understanding phenomena in fields, such as economics and trading, health care, urban planning and social sciences. From computer games to human societies, many natural and artificial phenomena can be represented as multi-agent systems.
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